Bacterial growth: a statistical physicist's guide

The carnivorous plant Genlisea harnesses active particle dynamics to prey on microfauna

Carnivory in plants is an unusual trait that has arisen multiple times, independently, throughout evolutionary history. Plants in the genus Genlisea are carnivorous and feed on microorganisms that live in soil using modified subterranean leaf structures (rhizophylls). A surprisingly broad array of microfauna has been observed in the plants' digestive chambers, including ciliates, amoebae, and soil mites. Here, we show, through experiments and simulations, that Genlisea exploit active matter physics to "rectify" bacterial swimming and establish a local flux of bacteria through the structured environment of the rhizophyll toward the plant's digestion vesicle. In contrast, macromolecular digestion products are free to diffuse away from the digestion vesicle and establish a concentration gradient of carbon sources to draw larger microorganisms further inside the plant. Our experiments and simulations show that this mechanism is likely to be a localized one and that no large-scale efflux of digested matter is present.

A stochastic model for the bacterial growth exhibiting staged growth, desynchronization, saturation and persistence

We consider a model of population growth based on the stochastic variation of the population size-controlled duplication of bacterial cells. It is shown that the proper choice of the control function allows for reproducing a variety of regimes: a logistic growth with saturation, a hindered growth typical for persistent bacterial systems, and a linear population growth detected for some mycobacterial populations. When supplied with the rectangular function having the width equal to the generation time, this approach represents the solution generalizing Rubinow's age-maturity model reproducing systems with desynchronization and saturation. The model's plausibility is confirmed by the direct comparison with real data for the growth of M. tuberculosis populations obtained with the BACTEC MGIT system under different conditions of growth synchronization.

A mathematical framework for the statistical interpretation of biological growth models

Biological entities are inherently dynamic. As such, various ecological disciplines use mathematical models to describe temporal evolution. Typically, growth curves are modelled as sigmoids, with the evolution modelled by ordinary differential equations. Among the various sigmoid models, the logistic, Gompertz and Richards equations are well-established and widely used for the purpose of fitting growth data in the fields of biology and ecology. The present paper puts forth a mathematical framework for the statistical analysis of population growth models. The analysis is based on a mathematical model of the population-environment relationship, the theoretical foundations of which are discussed in detail. By applying this theory, stochastic evolutionary equations are obtained, for which the logistic, Gompertz, Richards and Birch equations represent a limiting case. To substantiate the models of population growth dynamics, the results of numerical simulations are presented. It is demonstrated that a variety of population growth models can be addressed in a comparable manner. It is suggested that the discussed mathematical framework for statistical interpretation of the joint population-environment evolution represents a promising avenue for further research.

Infection fronts in randomly varying transmission-rate media

We numerically investigate the geometry and transport properties of infection fronts within the spatial SIR model in two dimensions. The model incorporates short-range correlated quenched random transmission rates. Our findings reveal that the critical average transmission rate for the steady-state propagation of the infection is overestimated by the naive mean-field homogenization. Furthermore, we observe that the velocity, profile, and harmfulness of the fronts, given a specific average transmission, are sensitive to the details of randomness. In particular, we find that the harmfulness of the front is larger the more uniform the transmission rate is, suggesting potential optimization in vaccination strategies under constraints like fixed average-transmission rates or limited vaccine resources. The large-scale geometry of the advancing fronts presents nevertheless robust universal features and, for a statistically isotropic and short-range correlated disorder, we get a roughness exponent α≈0.42±0.10 and a dynamical exponent z≈1.6±0.10, which are roughly compatible with the one-dimensional Kardar-Parisi-Zhang (KPZ) universality class. We find that the KPZ term and the disorder-induced effective noise are present and have a kinematic origin.

High-Throughput Determination of Infectious Virus Titers by Kinetic Measurement of Infection-Induced Changes in Cell Morphology

Infectivity assays are the key analytical technology for the development and manufacturing of virus-based therapeutics. Here, we introduce a novel assay format that utilizes label-free bright-field images to determine the kinetics of infection-dependent changes in cell morphology. In particular, cell rounding is directly proportional to the amount of infectious virus applied, enabling rapid determination of viral titers in relation to a standard curve. Our kinetic infectious virus titer (KIT) assay is stability-indicating and, due to its sensitive readout method, provides results within 24 h post-infection. Compared to traditional infectivity assays, which depend on a single readout of an infection endpoint, cumulated analysis of kinetic data by a fit model results in precise results (CV < 20%) based on only three wells per sample. This approach allows for a high throughput with ~400 samples processed by a single operator per week. We demonstrate the applicability of the KIT assay for the genetically engineered oncolytic VSV-GP, Newcastle disease virus (NDV), and parapoxvirus ovis (ORFV), but it can potentially be extended to a wide range of viruses that induce morphological changes upon infection. The versatility of this assay, combined with its independence from specific instruments or software, makes it a promising solution to overcome the analytical bottleneck in infectivity assays within the pharmaceutical industry and as a routine method in academic research.

Exploring spatial segregation induced by competition avoidance as driving mechanism for emergent coexistence in microbial communities

This study investigates the role of spatial segregation, prompted by competition avoidance, as a key mechanism for emergent coexistence within microbial communities. Recognizing these communities as complex adaptive systems, we challenge the sufficiency of mean-field pairwise interaction models, and we consider the impact of spatial dynamics. We developed an individual-based spatial simulation depicting bacterial movement through a pattern of random walks influenced by competition avoidance, leading to the formation of spatially segregated clusters. This model was integrated with a Lotka-Volterra metapopulation framework focused on competitive interactions. Our findings reveal that spatial segregation combined with low diffusion rates and high compositional heterogeneity among patches can lead to emergent coexistence in microbial communities. This reveals a novel mechanism underpinning the formation of stable, coexisting microbe clusters, which is nonetheless incapable of promoting coexistence in the case of isolated pairs of species. This study underscores the importance of considering spatial factors in understanding the dynamics of microbial ecosystems.

Quantifying massively parallel microbial growth with spatially mediated interactions

Quantitative understanding of microbial growth is an essential prerequisite for successful control of pathogens as well as various biotechnology applications. Even though the growth of cell populations has been extensively studied, microbial growth remains poorly characterised at the spatial level. Indeed, even isogenic populations growing at different locations on solid growth medium typically show significant location-dependent variability in growth. Here we show that this variability can be attributed to the initial physiological states of the populations, the interplay between populations interacting with their local environment and the diffusion of nutrients and energy sources coupling the environments. We further show how the causes of this variability change throughout the growth of a population. We use a dual approach, first applying machine learning regression models to discover that location dominates growth variability at specific times, and, in parallel, developing explicit population growth models to describe this spatial effect. In particular, treating nutrient and energy source concentration as a latent variable allows us to develop a mechanistic resource consumer model that captures growth variability across the shared environment. As a consequence, we are able to determine intrinsic growth parameters for each local population, removing confounders common to location-dependent variability in growth. Importantly, our explicit low-parametric model for the environment paves the way for massively parallel experimentation with configurable spatial niches for testing specific eco-evolutionary hypotheses.

Computer simulation study of nutrient-driven bacterial biofilm stratification

Here, employing computer simulation tools, we present a study on the development of a bacterial biofilm from a single starter cell on a flat inert surface overlaid by an aqueous solution containing nutrients. In our simulations, surface colonization involves an initial stage of two-dimensional cell proliferation to eventually transition to three-dimensional growth leading to the formation of biofilm colonies with characteristic three-dimensional semi-ellipsoids shapes. Thus, we have introduced the influence of the nutrient concentration on bacterial growth, and calculated the cell growth rate as a function of nutrient uptake, which in turn depends on local nutrient concentration in the vicinity of each bacterial cell. Our results show that the combination of cell growth and nutrient uptake and diffusion leads to the formation of stratified colonies containing an inner core in which nutrients are depleted and cells cannot grow or divide, surrounded by an outer, shallow crust in which cells have access to nutrients from the bulk medium and continue growing. This phenomenon is more apparent at high uptake rates that enable fast nutrient depletion. Our simulations also predict that the shape and internal structure of the biofilm are largely conditioned by the balance between nutrient diffusion and uptake.

Quantifying Geobacter sulfurreducens growth: A mathematical model based on acetate concentration as an oxidizing substrate

We developed a mathematical model to simulate dynamics associated with the proliferation of Geobacter and ultimately optimize cellular operation by analyzing the interaction of its components. The model comprises two segments: an initial part comprising a logistic form and a subsequent segment that incorporates acetate oxidation as a saturation term for the microbial nutrient medium. Given that four parameters can be obtained by minimizing the square root of the mean square error between experimental Geobacter growth and the mathematical model, the model underscores the importance of incorporating nonlinear terms. The determined parameter values closely align with experimental data, providing insights into the mechanisms that govern Geobacter proliferation. Furthermore, the model has been transformed into a scaleless equation with only two parameters to simplify the exploration of qualitative properties. This allowed us to conduct stability analysis of the fixed point and construct a co-dimension two bifurcation diagram.

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.

Biotechnological production of omega-3 fatty acids: current status and future perspectives

Omega-3 fatty acids, including alpha-linolenic acids (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA), have shown major health benefits, but the human body's inability to synthesize them has led to the necessity of dietary intake of the products. The omega-3 fatty acid market has grown significantly, with a global market from an estimated USD 2.10 billion in 2020 to a predicted nearly USD 3.61 billion in 2028. However, obtaining a sufficient supply of high-quality and stable omega-3 fatty acids can be challenging. Currently, fish oil serves as the primary source of omega-3 fatty acids in the market, but it has several drawbacks, including high cost, inconsistent product quality, and major uncertainties in its sustainability and ecological impact. Other significant sources of omega-3 fatty acids include plants and microalgae fermentation, but they face similar challenges in reducing manufacturing costs and improving product quality and sustainability. With the advances in synthetic biology, biotechnological production of omega-3 fatty acids via engineered microbial cell factories still offers the best solution to provide a more stable, sustainable, and affordable source of omega-3 fatty acids by overcoming the major issues associated with conventional sources. This review summarizes the current status, key challenges, and future perspectives for the biotechnological production of major omega-3 fatty acids.

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.

Facile Modification of Medical-Grade Silicone for Antimicrobial Effectiveness and Biocompatibility: A Potential Therapeutic Strategy against Bacterial Biofilms

A one-step modification of biomedical silicone tubing with N,N-dimethyltetradecylamine, C14, results in a composition designated WinGard-1 (WG-1, 1.1 wt % C14). A surface-active silicon-amine phase (SAP) is proposed to account for increased wettability and increased surface charge. To understand the mechanism of antimicrobial effectiveness, several procedures were employed to detect whether C14 leaching occurred. An immersion-growth (IG) test was developed that required knowing the bacterial Minimum Inhibitory Concentrations (MICs) and Minimum Biocidal Concentrations (MBCs). The C14 MIC and MBC for Gm- uropathogenic E. coli (UPEC), commonly associated with catheter-associated urinary tract infections (CAUTI), were 10 and 20 μg/mL, respectively. After prior immersion of WG-1 silicone segments in a growth medium from 1 to 28 d, the IG test for the medium showed normal growth for UPEC over 24 h, indicating that the concentration of C14 must be less than the MIC, 10 μg/mL. GC-MS and studies of the medium inside and outside a dialysis bag containing WG-1 silicone segments supported de minimis leaching. Consequently, a 5 log UPEC reduction (99.999% kill) in 24 h using the shake flask test (ASTM E2149) cannot be due to leaching and is ascribed to contact kill. Interestingly, although the MBC was greater than 100 μg/mL for Pseudomonas aeruginosa, WG-1 silicone affected an 80% reduction via a 24 h shake flask test. For other bacteria and Candida albicans, greater than 99.9% shake flask kill may be understood by proposing increased wettability and concentration of charge illustrated in the TOC. De minimis leaching places WG-1 silicone at an advantage over conventional anti-infectives that rely on leaching of an antibiotic or heavy metals such as silver. The facile process for preparation of WG-1 silicone combined with biocidal effectiveness comprises progress toward the goals of device designation from the FDA for WG-1 and clearance.

Cluster analysis and forecasting of viruses incidence growth curves: Application to SARS-CoV-2

The sanitary emergency caused by COVID-19 has compromised countries and generated a worldwide health and economic crisis. To provide support to the countries' responses, numerous lines of research have been developed. The spotlight was put on effectively and rapidly diagnosing and predicting the evolution of the pandemic, one of the most challenging problems of the past months. This work contributes to the existing literature by developing a two-step methodology to analyze the transmission rate, designing models applied to territories with similar pandemic behavior characteristics. Virus transmission is considered as bacterial growth curves to understand the spread of the virus and to make predictions about its future evolution. Hence, an analytical clustering procedure is first applied to create groups of locations where the virus transmission rate behaved similarly in the different outbreaks. A curve decomposition process based on an iterative polynomial process is then applied, obtaining meaningful forecasting features. Information of the territories belonging to the same cluster is merged to build models capable of simultaneously predicting the 14-day incidence in several locations using Evolutionary Artificial Neural Networks. The methodology is applied to Andalusia (Spain), although it is applicable to any region across the world. Individual models trained for a specific territory are carried out for comparison purposes. The results demonstrate that this methodology achieves statistically similar, or even better, performance for most of the locations. In addition to being extremely competitive, the main advantage of the proposal lies in its complexity cost reduction. The total number of parameters to be estimated is reduced up to 93.51% for the short term and 93.31% for the mid-term forecasting, respectively. Moreover, the number of required models is reduced by 73.53% and 58.82% for the short- and mid-term forecasting horizons.

Exposure to High Dosage of Gold Nanoparticles Accelerates Growth Rate by Modulating Ribosomal Protein Expression

Gold nanoparticles (AuNPs) have been utilized in various biomedical applications including diagnostics and drug delivery. However, the cellular and metabolic responses of cells to these particles remain poorly characterized. In this study, we used bacteria (Escherichia coli and Bacillus subtilis) and a fungus (Saccharomyces cerevisiae) as model organisms to investigate the cellular and metabolic effects of exposure to different concentrations of citrate-capped spherical AuNPs with diameters of 5 and 10 nm. In different growth media, the synthesized AuNPs displayed stability and microorganisms exhibited uniform levels of uptake. Exposure to a high concentration of AuNPs (1012 particles) resulted in a reduced cell division time and a 2-fold increase in cell density in both bacteria and fungus. The exposed cells exhibited a decrease in average cell size and an increase in the expression of FtsZ protein (cell division marker), further supporting an accelerated growth rate. Notably, exposure to such a high concentration of AuNPs did not induce DNA damage, envelope stress, or a general stress response in bacteria. Differential whole proteome analysis revealed modulation of ribosomal protein expression upon exposure to AuNPs in both E. coli and S. cerevisiae. Interestingly, the accelerated growth observed upon exposure to AuNPs was sensitive to sub-minimum inhibitory concentration (sub-MIC) concentration of drugs that specifically target ribosome assembly and recycling. Based upon these findings, we hypothesize that exposure to high concentrations of AuNPs induces stress on the translation machinery. This leads to an increase in the protein synthesis rate by modulating ribosome assembly, which results in the rapid proliferation of cells.

Reduction of bioavailability and phytotoxicity effect of cadmium in soil by microbial-induced carbonate precipitation using metabolites of ureolytic bacterium Ochrobactrum sp. POC9

The application of ureolytic bacteria for bioremediation of soil contaminated with heavy metals, including cadmium (Cd), allows for the efficient immobilization of heavy metals by precipitation or coprecipitation with carbonates. Microbially-induced carbonate precipitation process may be useful also in the case of the cultivation of crop plants in various agricultural soils with trace but legally permissible Cd concentrations, which may be still uptaken by plants. This study aimed to investigate the influence of soil supplementation with metabolites containing carbonates (MCC) produced by the ureolytic bacterium Ochrobactrum sp. POC9 on the Cd mobility in the soil as well as on the Cd uptake efficiency and general condition of crop plants (Petroselinum crispum). In the frame of the conducted studies (i) carbonate productivity of the POC9 strain, (ii) the efficiency of Cd immobilization in soil supplemented with MCC, (iii) crystallization of cadmium carbonate in the soil enriched with MCC, (iv) the effect of MCC on the physico-chemical and microbiological properties of soil, and (v) the effect of changes in soil properties on the morphology, growth rate, and Cd-uptake efficiency of crop plants were investigated. The experiments were conducted in soil contaminated with a low concentration of Cd to simulate the natural environmental conditions. Soil supplementation with MCC significantly reduced the bioavailability of Cd in soil with regard to control variants by about 27-65% (depending on the volume of MCC) and reduced the Cd uptake by plants by about 86% and 74% in shoots and roots, respectively. Furthermore, due to the decrease in soil toxicity and improvement of soil nutrition with other metabolites produced during the urea degradation (MCC), some microbiological properties of soil (quantity and activity of soil microorganisms), as well as the general condition of plants, were also significantly improved. Soil supplementation with MCC enabled efficient Cd stabilization and significantly reduced its toxicity for soil microbiota and plants. Thus, MCC produced by POC9 strain may be used not only as an effective Cd immobilizer in soil but also as a microbe and plant stimulators.

Active layer dynamics drives a transition to biofilm fingering

The emergence of spatial organisation in biofilm growth is one of the most fundamental topics in biofilm biophysics and microbiology. It has long been known that growing biofilms can adopt smooth or rough interface morphologies, depending on the balance between nutrient supply and microbial growth; this 'fingering' transition has been linked with the average width of the 'active layer' of growing cells at the biofilm interface. Here we use long-time individual-based simulations of growing biofilms to investigate in detail the driving factors behind the biofilm-fingering transition. We show that the transition is associated with dynamical changes in the active layer. Fingering happens when gaps form in the active layer, which can cause local parts of the biofilm interface to pin, or become stationary relative to the moving front. Pinning can be transient or permanent, leading to different biofilm morphologies. By constructing a phase diagram for the transition, we show that the controlling factor is the magnitude of the relative fluctuations in the active layer thickness, rather than the active layer thickness per se. Taken together, our work suggests a central role for active layer dynamics in controlling the pinning of the biofilm interface and hence biofilm morphology.

Vertical growth dynamics of biofilms

During the biofilm life cycle, bacteria attach to a surface and then reproduce, forming crowded, growing communities. Many theoretical models of biofilm growth dynamics have been proposed; however, difficulties in accurately measuring biofilm height across relevant time and length scales have prevented testing these models, or their biophysical underpinnings, empirically. Using white light interferometry, we measure the heights of microbial colonies with nanometer precision from inoculation to their final equilibrium height, producing a detailed empirical characterization of vertical growth dynamics. We propose a heuristic model for vertical growth dynamics based on basic biophysical processes inside a biofilm: diffusion and consumption of nutrients and growth and decay of the colony. This model captures the vertical growth dynamics from short to long time scales (10 min to 14 d) of diverse microorganisms, including bacteria and fungi.

Stability of Pattern Formation in Systems with Dynamic Source Regions

We explain the principles of gene expression pattern stabilization in systems of interacting, diffusible morphogens, with dynamically established source regions. Using a reaction-diffusion model with a step-function production term, we identify the phase transition between low-precision indeterminate patterning and the phase in which a traveling, well-defined contact zone between two domains is formed. Our model analytically explains single- and two-gene domain dynamics and provides pattern stability conditions for all possible two-gene regulatory network motifs.

Computational protein design repurposed to explore enzyme vitality and help predict antibiotic resistance

In response to antibiotics that inhibit a bacterial enzyme, resistance mutations inevitably arise. Predicting them ahead of time would aid target selection and drug design. The simplest resistance mechanism would be to reduce antibiotic binding without sacrificing too much substrate binding. The property that reflects this is the enzyme "vitality", defined here as the difference between the inhibitor and substrate binding free energies. To predict such mutations, we borrow methodology from computational protein design. We use a Monte Carlo exploration of mutation space and vitality changes, allowing us to rank thousands of mutations and identify ones that might provide resistance through the simple mechanism considered. As an illustration, we chose dihydrofolate reductase, an essential enzyme targeted by several antibiotics. We simulated its complexes with the inhibitor trimethoprim and the substrate dihydrofolate. 20 active site positions were mutated, or "redesigned" individually, then in pairs or quartets. We computed the resulting binding free energy and vitality changes. Out of seven known resistance mutations involving active site positions, five were correctly recovered. Ten positions exhibited mutations with significant predicted vitality gains. Direct couplings between designed positions were predicted to be small, which reduces the combinatorial complexity of the mutation space to be explored. It also suggests that over the course of evolution, resistance mutations involving several positions do not need the underlying point mutations to arise all at once: they can appear and become fixed one after the other.

New understanding of multidrug efflux and permeation in antibiotic resistance, persistence, and heteroresistance

Antibiotics effective against Gram-negative ESKAPE pathogens are a critical area of unmet need. Infections caused by these pathogens are not only difficult to treat but finding new therapies to overcome Gram-negative resistance is also a challenge. There are not enough antibiotics in development that target the most dangerous pathogens and there are not enough novel drugs in the pipeline. The major obstacle in the antibiotic discovery pipeline is the lack of understanding of how to breach antibiotic permeability barriers of Gram-negative pathogens. These barriers are created by active efflux pumps acting across both the inner and the outer membranes. Overproduction of efflux pumps alone or together with either modification of the outer membrane or antibiotic-inactivating enzymes and target mutations contribute to clinical levels of antibiotics resistance. Recent efforts have generated significant advances in the rationalization of compound efflux and permeation across the cell envelopes of Gram-negative pathogens. Combined with earlier studies and novel mathematical models, these efforts have led to a multilevel understanding of how antibiotics permeate these barriers and how multidrug efflux and permeation contribute to the development of antibiotic resistance and heteroresistance. Here, we discuss the new developments in this area.

Tilt-induced polar order and topological defects in growing bacterial populations

Rod-shaped bacteria, such as Escherichia coli, commonly live forming mounded colonies. They initially grow two-dimensionally on a surface and finally achieve three-dimensional growth. While it was recently reported that three-dimensional growth is promoted by topological defects of winding number +1/2 in populations of motile bacteria, how cellular alignment plays a role in nonmotile cases is largely unknown. Here, we investigate the relevance of topological defects in colony formation processes of nonmotile E. coli populations, and found that both ±1/2 topological defects contribute to the three-dimensional growth. Analyzing the cell flow in the bottom layer of the colony, we observe that +1/2 defects attract cells and -1/2 defects repel cells, in agreement with previous studies on motile cells, in the initial stage of the colony growth. However, later, cells gradually flow toward -1/2 defects as well, exhibiting a sharp contrast to the existing knowledge. By investigating three-dimensional cell orientations by confocal microscopy, we find that vertical tilting of cells is promoted near the defects. Crucially, this leads to the emergence of a polar order in the otherwise nematic two-dimensional cell orientation. We extend the theory of active nematics by incorporating this polar order and the vertical tilting, which successfully explains the influx toward -1/2 defects in terms of a polarity-induced force. Our work reveals that three-dimensional cell orientations may result in qualitative changes in properties of active nematics, especially those of topological defects, which may be generically relevant in active matter systems driven by cellular growth instead of self-propulsion.

Model for Quorum-Sensing Mediated Stochastic Biofilm Nucleation

Surface-attached bacterial biofilms cause disease and industrial biofouling, as well as being widespread in the natural environment. Density-dependent quorum sensing is one of the mechanisms implicated in biofilm initiation. Here we present and analyze a model for quorum-sensing triggered biofilm initiation. In our model, individual, planktonic bacteria adhere to a surface, proliferate, and undergo a collective transition to a biofilm phenotype. This model predicts a stochastic transition between a loosely attached, finite layer of bacteria near the surface and a growing biofilm. The transition is governed by two key parameters: the collective transition density relative to the carrying capacity and the immigration rate relative to the detachment rate. Biofilm initiation is complex, but our model suggests that stochastic nucleation phenomena may be relevant.

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.

Density-dependent effects are the main determinants of variation in growth dynamics between closely related bacterial strains

Although closely related, bacterial strains from the same species show significant diversity in their growth and death dynamics. Yet, our understanding of the relationship between the kinetic parameters that dictate these dynamics is still lacking. Here, we measured the growth and death dynamics of 11 strains of Escherichia coli originating from different hosts and show that the growth patterns are clustered into three major classes with typical growth rates, maximal fold change, and death rates. To infer the underlying phenotypic parameters that govern the dynamics, we developed a phenomenological mathematical model that accounts not only for growth rate and its dependence on resource availability, but also for death rates and density-dependent growth inhibition. We show that density-dependent growth is essential for capturing the variability in growth dynamics between the strains. Indeed, the main parameter determining the dynamics is the typical density at which they slow down their growth, rather than the maximal growth rate or death rate. Moreover, we show that the phenotypic landscape resides within a two-dimensional plane spanned by resource utilization efficiency, death rate, and density-dependent growth inhibition. In this phenotypic plane, we identify three clusters that correspond to the growth pattern classes. Overall, our results reveal the tradeoffs between growth parameters that constrain bacterial adaptation.

A computational model for microbial colonization of an antifouling surface

Biofouling of marine surfaces such as ship hulls is a major industrial problem. Antifouling (AF) paints delay the onset of biofouling by releasing biocidal chemicals. We present a computational model for microbial colonization of a biocide-releasing AF surface. Our model accounts for random arrival from the ocean of microorganisms with different biocide resistance levels, biocide-dependent proliferation or killing, and a transition to a biofilm state. Our computer simulations support a picture in which biocide-resistant microorganisms initially form a loosely attached layer that eventually transitions to a growing biofilm. Once the growing biofilm is established, immigrating microorganisms are shielded from the biocide, allowing more biocide-susceptible strains to proliferate. In our model, colonization of the AF surface is highly stochastic. The waiting time before the biofilm establishes is exponentially distributed, suggesting a Poisson process. The waiting time depends exponentially on both the concentration of biocide at the surface and the rate of arrival of resistant microorganisms from the ocean. Taken together our results suggest that biofouling of AF surfaces may be intrinsically stochastic and hence unpredictable, but immigration of more biocide-resistant species, as well as the biological transition to biofilm physiology, may be important factors controlling the time to biofilm establishment.

Self-potential time series reveal emergent behavior in soil organic matter dynamics

The active cycling of carbon between soil organic matter and the atmosphere is of critical importance to global climate change. An extensive body of research exists documenting the capricious nature of soil organic matter (SOM) dynamics, which is symptomatic of an intricate network of interactions between diverse groups of heterotrophic microorganisms, complex organic substrates, and highly variable local environmental conditions. These attributes are consistent with elements of complex system theory and the temporal evolution of otherwise unpredictable patterns of behavior that emerge from long range dependency on initial conditions. Here we show that vertical depth profile of self-potential (SP) time series measurements responds in a quantitative manner to variations in soil moisture, SOM concentrations, and relative rates of microbial activity. Application of detrended fluctuation analysis (DFA) of self potential time series data is shown additionally to reveal the presence of long-range dependence and emergence of anomalous electrochemical diffusion behavior, both of which diminish with depth as SOM specific energy densities decline.

Cellular Sensing Governs the Stability of Chemotactic Fronts

In contexts ranging from embryonic development to bacterial ecology, cell populations migrate chemotactically along self-generated chemical gradients, often forming a propagating front. Here, we theoretically show that the stability of such chemotactic fronts to morphological perturbations is determined by limitations in the ability of individual cells to sense and thereby respond to the chemical gradient. Specifically, cells at bulging parts of a front are exposed to a smaller gradient, which slows them down and promotes stability, but they also respond more strongly to the gradient, which speeds them up and promotes instability. We predict that this competition leads to chemotactic fingering when sensing is limited at too low chemical concentrations. Guided by this finding and by experimental data on E. coli chemotaxis, we suggest that the cells' sensory machinery might have evolved to avoid these limitations and ensure stable front propagation. Finally, as sensing of any stimuli is necessarily limited in living and active matter in general, the principle of sensing-induced stability may operate in other types of directed migration such as durotaxis, electrotaxis, and phototaxis.

Bifunctional conducting polymer matrices with antibacterial and neuroprotective effects

Current trends in the field of neural tissue engineering include the design of advanced biomaterials combining excellent electrochemical performance with versatile biological characteristics. The purpose of this work was to develop an antibacterial and neuroprotective coating based on a conducting polymer - poly(3,4-ethylenedioxypyrrole) (PEDOP), loaded with an antibiotic agent - tetracycline (Tc). Employing an electrochemical technique to immobilize Tc within a growing polymer matrix allowed to fabricate robust PEDOP/Tc coatings with a high charge storage capacity (63.65 ± 6.05 mC/cm2), drug release efficiency (629.4 µg/cm2 ± 62.7 µg/cm2), and low charge transfer resistance (2.4 ± 0.1 kΩ), able to deliver a stable electrical signal. PEDOP/Tc were found to exhibit strong antimicrobial effects against Gram-negative bacteria Escherichia coli, expressed through negligible adhesion, reduction in viability, and a characteristic elongation of bacterial cells. Cytocompatibility and neuroprotective effects were evaluated using a rat neuroblastoma B35 cell line, and were analyzed using MTT, cell cycle, and Annexin-V apoptosis assays. The presence of Tc was found to enhance neural cell viability and neurite outgrowth. The results confirmed that PEDOP/Tc can serve as an efficient neural electrode coating able to enhance charge transfer, as well as to exhibit bifunctional biological characteristics, different for eukaryotic and prokaryotic cells.

Chemotactic smoothing of collective migration

Collective migration-the directed, coordinated motion of many self-propelled agents-is a fascinating emergent behavior exhibited by active matter with functional implications for biological systems. However, how migration can persist when a population is confronted with perturbations is poorly understood. Here, we address this gap in knowledge through studies of bacteria that migrate via directed motion, or chemotaxis, in response to a self-generated nutrient gradient. We find that bacterial populations autonomously smooth out large-scale perturbations in their overall morphology, enabling the cells to continue to migrate together. This smoothing process arises from spatial variations in the ability of cells to sense and respond to the local nutrient gradient-revealing a population-scale consequence of the manner in which individual cells transduce external signals. Altogether, our work provides insights to predict, and potentially control, the collective migration and morphology of cellular populations and diverse other forms of active matter.

Tracking the stochastic growth of bacterial populations in microfluidic droplets

Bacterial growth in microfluidic droplets is relevant in biotechnology, in microbial ecology, and in understanding stochastic population dynamics in small populations. However, it has proved challenging to automate measurement of absolute bacterial numbers within droplets, forcing the use of proxy measures for population size. Here we present a microfluidic device and imaging protocol that allows high-resolution imaging of thousands of droplets, such that individual bacteria stay in the focal plane and can be counted automatically. Using this approach, we track the stochastic growth of hundreds of replicateEscherichia colipopulations within droplets. We find that, for early times, the statistics of the growth trajectories obey the predictions of the Bellman-Harris model, in which there is no inheritance of division time. Our approach should allow further testing of models for stochastic growth dynamics, as well as contributing to broader applications of droplet-based bacterial culture.

Unified analysis of topological defects in 2D systems of active and passive disks

We provide a comprehensive quantitative analysis of localized and extended topological defects in the steady state of 2D passive and active repulsive Brownian disk systems. We show that, both in and out-of-equilibrium, the passage from the solid to the hexatic is driven by the unbinding of dislocations, in quantitative agreement with the KTHNY singularity. Instead, extended clusters of defects largely dominate below the solid-hexatic critical line. The latter percolate in the liquid phase very close to the hexatic-liquid transition, both for continuous and discontinuous transitions, in the homogeneous liquid regime. At critical percolation the clusters of defects are fractal with statistical and geometric properties that are independent of the activity and compatible with the universality class of uncorrelated critical percolation. We also characterize the spatial organization of point-like defects and we show that the disclinations are not free, but rather always very near more complex defect structures. At high activity, the bulk of the dense phase generated by Motility-Induced Phase Separation is characterized by a density of point-like defects, and statistics and morphology of defect clusters, set by the amount of activity and not the packing fraction. Hexatic domains within the dense phase are separated by grain-boundaries along which a finite network of topological defects resides, interrupted by gas bubbles in cavitation. This structure is dynamic in the sense that the defect network allows for an unzipping mechanism that leaves free space for gas bubbles to appear, close, and even be released into the dilute phase.

Dimensionless parameter predicts bacterial prodrug success

Understanding mechanisms of antibiotic failure is foundational to combating the growing threat of multidrug-resistant bacteria. Prodrugs-which are converted into a pharmacologically active compound after administration-represent a growing class of therapeutics for treating bacterial infections but are understudied in the context of antibiotic failure. We hypothesize that strategies that rely on pathogen-specific pathways for prodrug conversion are susceptible to competing rates of prodrug activation and bacterial replication, which could lead to treatment escape and failure. Here, we construct a mathematical model of prodrug kinetics to predict rate-dependent conditions under which bacteria escape prodrug treatment. From this model, we derive a dimensionless parameter we call the Bacterial Advantage Heuristic (BAH) that predicts the transition between prodrug escape and successful treatment across a range of time scales (1-104  h), bacterial carrying capacities (5 × 104 -105  CFU/µl), and Michaelis constants (KM  = 0.747-7.47 mM). To verify these predictions in vitro, we use two models of bacteria-prodrug competition: (i) an antimicrobial peptide hairpin that is enzymatically activated by bacterial surface proteases and (ii) a thiomaltose-conjugated trimethoprim that is internalized by bacterial maltodextrin transporters and hydrolyzed by free thiols. We observe that prodrug failure occurs at BAH values above the same critical threshold predicted by the model. Furthermore, we demonstrate two examples of how failing prodrugs can be rescued by decreasing the BAH below the critical threshold via (i) substrate design and (ii) nutrient control. We envision such dimensionless parameters serving as supportive pharmacokinetic quantities that guide the design and administration of prodrug therapeutics.

Metabolic profiling reveals nutrient preferences during carbon utilization in Bacillus species

The genus Bacillus includes species with diverse natural histories, including free-living nonpathogenic heterotrophs such as B. subtilis and host-dependent pathogens such as B. anthracis (the etiological agent of the disease anthrax) and B. cereus, a cause of food poisoning. Although highly similar genotypically, the ecological niches of these three species are mutually exclusive, which raises the untested hypothesis that their metabolism has speciated along a nutritional tract. Here, we developed a pipeline for quantitative total assessment of the use of diverse sources of carbon for general metabolism to better appreciate the "culinary preferences" of three distinct Bacillus species, as well as related Staphylococcus aureus. We show that each species has widely varying metabolic ability to utilize diverse sources of carbon that correlated to their ecological niches. This approach was applied to the growth and survival of B. anthracis in a blood-like environment and find metabolism shifts from sugar to amino acids as the preferred source of energy. Finally, various nutrients in broth and host-like environments are identified that may promote or interfere with bacterial metabolism during infection.

Evaluating comparative β-glucan production aptitude of Saccharomyces cerevisiae, Aspergillus oryzae, Xanthomonas campestris, and Bacillus natto

β-glucan is a natural polysaccharide derivative composed of a group of glucose monomers with β-glycoside bonds that can be synthesized intra- or extra-cellular by various microorganisms such as yeasts, bacteria, and moulds. The study aimed to discover the potential of various microorganisms such as Saccharomyces cerevisiae, Aspergillus oryzae, Xanthomonas campestris, and Bacillus natto in producing β-glucan. The experimental method used and the data were analyzed descriptively. The four microorganisms above were cultured under a submerged state in Yeast glucose (YG) broth for 120 h at 30 °C with 200 rpm agitation. During the growth, several parameters were examined including total population by optical density, the pH, and glucose contents of growth media. β-glucan was extracted using acid-alkaline methods from the growth media then the weight was measured. The results showed that S. cerevisiae, A. oryzae X. campestris, and B. natto were prospective for β-glucans production in submerged fermentation up to 120 h. The highest β-glucans yield was shown by B. natto (20.38%) with the β-glucans mass of 1.345 ± 0.08 mg and globular diameter of 600 μm. The highest β-glucan mass was achieved by A. oryzae of 82.5 ± 0.03 mg with the total population in optical density of 0.1246, a final glucose level of 769 ppm, the pH of 6.67, and yield of 13.97% with a globular diameter of 1400 μm.

Suboptimal resource allocation in changing environments constrains response and growth in bacteria

To respond to fluctuating conditions, microbes typically need to synthesize novel proteins. As this synthesis relies on sufficient biosynthetic precursors, microbes must devise effective response strategies to manage depleting precursors. To better understand these strategies, we investigate the active response of Escherichia coli to changes in nutrient conditions, connecting transient gene expression to growth phenotypes. By synthetically modifying gene expression during changing conditions, we show how the competition by genes for the limited protein synthesis capacity constrains cellular response. Despite this constraint cells substantially express genes that are not required, trapping them in states where precursor levels are low and the genes needed to replenish the precursors are outcompeted. Contrary to common modeling assumptions, our findings highlight that cells do not optimize growth under changing environments but rather exhibit hardwired response strategies that may have evolved to promote fitness in their native environment. The constraint and the suboptimality of the cellular response uncovered provide a conceptual framework relevant for many research applications, from the prediction of evolution to the improvement of gene circuits in biotechnology.

Interparticle Adhesion Regulates the Surface Roughness of Growing Dense Three-Dimensional Active Particle Aggregates

Activity and self-generated motion are fundamental features observed in many living and nonliving systems. Given that interparticle adhesive forces can regulate particle dynamics, we investigate how interparticle adhesion strength controls the boundary growth and roughness of active particle aggregates. Using particle based simulations incorporating both activity (birth, death, and growth) and systematic physical interactions (elasticity and adhesion), we establish that interparticle adhesion strength (f^ad) controls the surface roughness of a densely packed three-dimensional(3D) active particle aggregate expanding into a highly viscous medium. We discover that the surface roughness of a 3D active particle aggregate increases in proportion to the interparticle adhesion strength (f^ad) and show that asymmetry in the radial and transverse active particle mean-squared displacement (MSD) suppresses 3D surface roughness at lower adhesion strengths. By analyzing the statistical properties of particle displacements at the aggregate periphery, we determine that the 3D surface roughness is driven by the movement of active particle toward the core at high interparticle adhesion strengths. Our results elucidate the physics controlling the expansion of adhesive 3D active particle collectives into a highly viscous medium, with implications into understanding stochastic interface growth in active matter systems characterized by self-generation of particles.

Evaluation of the Potential of Marine Algae Extracts as a Source of Functional Ingredients Using Zebrafish as Animal Model for Aquaculture

Research on immunotherapeutic agents has become a focus for the treatment of fish diseases. The ability of algae to produce secondary metabolites of potential interest as immunotherapeutics has been documented. The present research intended to assess antiviral and antibacterial activities of macro- and microalgae extracts against viral and bacterial pathogens and explore their immunomodulatory potential using zebrafish (Danio rerio) larvae as a model organism. The cytotoxicity and antiviral activity of eight methanolic and ethanolic extracts from two macroalgae (Fucus vesiculosus, Ulva rigida) and two microalgae (Nannochloropsis gaditana, Chlorella sp.) were analyzed in established fish cell lines. Six extracts were selected to evaluate antibacterial activity by disk diffusion and growth inhibition assays. The three most promising extracts were characterized in terms of fatty acid composition, incorporated at 1% into a plant-based diet, and evaluated their effect on zebrafish immune response and intestinal morphology in a short-term feeding trial. All extracts exhibited in vitro antiviral activity against viral hemorrhagic septicemia and/or infectious pancreatic necrosis viruses. Methanolic extracts from F. vesiculosus and U. rigida were richer in saturated fatty acids and exhibited in vitro antibacterial action against several bacteria. Most promising results were obtained in vivo with F. vesiculosus methanol extract, which exerted an anti-inflammatory action when incorporated alone into diets and induced pro-inflammatory cytokine expression, when combined with the other extracts. Moreover, dietary inclusion of the extracts improved intestinal morphology. In summary, the results obtained in this study support the potential of algae as natural sources of bioactive compounds for the aquaculture industry.

Pseudomonas Strains Induce Transcriptional and Morphological Changes and Reduce Root Colonization of Verticillium spp

Phytopathogenic Verticillia cause Verticillium wilt on numerous economically important crops. Plant infection begins at the roots, where the fungus is confronted with rhizosphere inhabiting bacteria. The effects of different fluorescent pseudomonads, including some known biocontrol agents of other plant pathogens, on fungal growth of the haploid Verticillium dahliae and/or the amphidiploid Verticillium longisporum were compared on pectin-rich medium, in microfluidic interaction channels, allowing visualization of single hyphae, or on Arabidopsis thaliana roots. We found that the potential for formation of bacterial lipopeptide syringomycin resulted in stronger growth reduction effects on saprophytic Aspergillus nidulans compared to Verticillium spp. A more detailed analyses on bacterial-fungal co-cultivation in narrow interaction channels of microfluidic devices revealed that the strongest inhibitory potential was found for Pseudomonas protegens CHA0, with its inhibitory potential depending on the presence of the GacS/GacA system controlling several bacterial metabolites. Hyphal tip polarity was altered when V. longisporum was confronted with pseudomonads in narrow interaction channels, resulting in a curly morphology instead of straight hyphal tip growth. These results support the hypothesis that the fungus attempts to evade the bacterial confrontation. Alterations due to co-cultivation with bacteria could not only be observed in fungal morphology but also in fungal transcriptome. P. protegens CHA0 alters transcriptional profiles of V. longisporum during 2 h liquid media co-cultivation in pectin-rich medium. Genes required for degradation of and growth on the carbon source pectin were down-regulated, whereas transcripts involved in redox processes were up-regulated. Thus, the secondary metabolite mediated effect of Pseudomonas isolates on Verticillium species results in a complex transcriptional response, leading to decreased growth with precautions for self-protection combined with the initiation of a change in fungal growth direction. This interplay of bacterial effects on the pathogen can be beneficial to protect plants from infection, as shown with A. thaliana root experiments. Treatment of the roots with bacteria prior to infection with V. dahliae resulted in a significant reduction of fungal root colonization. Taken together we demonstrate how pseudomonads interfere with the growth of Verticillium spp. and show that these bacteria could serve in plant protection.

Development of Biopolymeric Hybrid Scaffold-Based on AAc/GO/nHAp/TiO2 Nanocomposite for Bone Tissue Engineering: In-Vitro Analysis

Bone tissue engineering is an advanced field for treatment of fractured bones to restore/regulate biological functions. Biopolymeric/bioceramic-based hybrid nanocomposite scaffolds are potential biomaterials for bone tissue because of biodegradable and biocompatible characteristics. We report synthesis of nanocomposite based on acrylic acid (AAc)/guar gum (GG), nano-hydroxyapatite (HAp NPs), titanium nanoparticles (TiO2 NPs), and optimum graphene oxide (GO) amount via free radical polymerization method. Porous scaffolds were fabricated through freeze-drying technique and coated with silver sulphadiazine. Different techniques were used to investigate functional group, crystal structural properties, morphology/elemental properties, porosity, and mechanical properties of fabricated scaffolds. Results show that increasing amount of TiO2 in combination with optimized GO has improved physicochemical and microstructural properties, mechanical properties (compressive strength (2.96 to 13.31 MPa) and Young's modulus (39.56 to 300.81 MPa)), and porous properties (pore size (256.11 to 107.42 μm) and porosity (79.97 to 44.32%)). After 150 min, silver sulfadiazine release was found to be ~94.1%. In vitro assay of scaffolds also exhibited promising results against mouse pre-osteoblast (MC3T3-E1) cell lines. Hence, these fabricated scaffolds would be potential biomaterials for bone tissue engineering in biomedical engineering.

Delivery of antisense oligonucleotides using multi-layer coated gold nanoparticles to methicillin-resistant S. aureus for combinatorial treatment

The spread of multidrug-resistant (MDR) bacterial infections has become a serious global threat. We introduce multi-layer coated gold nanoparticles (MLGNPs) delivering antisense oligonucleotides (ASOs) targeting the resistance gene of methicillin-resistant Staphylococcus aureus (MRSA), as a selective antimicrobial by restoring susceptibility. MLGNPs were prepared by multi-step surface immobilization of gold nanoparticles (GNPs) with polyethylenimine (PEI) and loaded with ASO targeting the mecA gene. The MLGNPs were shown to be efficiently internalized into various types of Gram-positive bacteria, including MRSA, Staphylococcus epidermidis, and Bacillus subtilis, which was superior to single-layer coated GNPs and free PEI polymer. The delivery of MLGNPs into MRSA resulted in up to 74% silencing of the mecA gene with high selectivity, in a dose-dependent manner. The treatment of MLGNPs to MRSA in the presence of oxacillin, a beta-lactam antibiotic, showed major suppression (~71%) of bacterial growth, due to the recovery of antibacterial sensitivity. Furthermore, the treatment of MLGNPs in a complex system showed preferential uptake into bacteria over mammalian cells, demonstrating the suitable characteristics of MLGNPs for selective delivery into bacteria. The current approach can be potentially applied for targeting various types of MDR bacterial infections by specific silencing of a resistance gene, as a combinatorial therapeutic used with conventional antibiotics.

Polymeric Nanoparticles for Antimicrobial Therapies: An Up-To-Date Overview

Despite the many advancements in the pharmaceutical and medical fields and the development of numerous antimicrobial drugs aimed to suppress and destroy pathogenic microorganisms, infectious diseases still represent a major health threat affecting millions of lives daily. In addition to the limitations of antimicrobial drugs associated with low transportation rate, water solubility, oral bioavailability and stability, inefficient drug targeting, considerable toxicity, and limited patient compliance, the major cause for their inefficiency is the antimicrobial resistance of microorganisms. In this context, the risk of a pre-antibiotic era is a real possibility. For this reason, the research focus has shifted toward the discovery and development of novel and alternative antimicrobial agents that could overcome the challenges associated with conventional drugs. Nanotechnology is a possible alternative, as there is significant evidence of the broad-spectrum antimicrobial activity of nanomaterials and nanoparticles in particular. Moreover, owing to their considerable advantages regarding their efficient cargo dissolving, entrapment, encapsulation, or surface attachment, the possibility of forming antimicrobial groups for specific targeting and destruction, biocompatibility and biodegradability, low toxicity, and synergistic therapy, polymeric nanoparticles have received considerable attention as potential antimicrobial drug delivery agents. In this context, the aim of this paper is to provide an up-to-date overview of the most recent studies investigating polymeric nanoparticles designed for antimicrobial therapies, describing both their targeting strategies and their effects.

Passive Microwave Biosensor for Real-Time Monitoring of Subsurface Bacterial Growth

A real-time and label-free microstrip sensor capable of detecting and monitoring subsurface growth of Escherichia coli (E. coli) on solid growth media such as Luria-Bertani (LB) agar is presented. The microwave ring resonator was designed to operate at 1.76 GHz to detect variations in the dielectric properties such as permittivity and loss tangent to monitor bacterial growth. The sensor demonstrated high efficiency in monitoring subsurface dynamics of E. coli growth between two layers of LB agar. The resonant amplitude variations (Δ Amplitude (dB)) were recorded for different volumes of E. coli (3 μL and 9 μL) and compared to control without E. coli for 36 hours. The control showed a maximum amplitude variation of 0.037 dB, which was selected as a threshold to distinguish between the presence and absence of E. coli growth. The measured results by sensors were further supported by microscopic images. It is worth noticing that the amplitude variations fit well with the Gompertz growth model. The rate of amplitude change correlating bacteria growth rate was calculated as 0.08 and 0.13 dB/hr. for 3 μL and 9 μL of E. coli, respectively. This work is a proof of concept to demonstrate the capability of microwave sensors to detect and monitor subsurface bacterial growth.

Confinement-induced self-organization in growing bacterial colonies

We investigate the emergence of global alignment in colonies of dividing rod-shaped cells under confinement. Using molecular dynamics simulations and continuous modeling, we demonstrate that geometrical anisotropies in the confining environment give rise to an imbalance in the normal stresses, which, in turn, drives a collective rearrangement of the cells. This behavior crucially relies on the colony's solid-like mechanical response at short time scales and can be recovered within the framework of active hydrodynamics upon modeling bacterial colonies as growing viscoelastic gels characterized by Maxwell-like stress relaxation.

Development of Arabinoxylan-Reinforced Apple Pectin/Graphene Oxide/Nano-Hydroxyapatite Based Nanocomposite Scaffolds with Controlled Release of Drug for Bone Tissue Engineering: In-Vitro Evaluation of Biocompatibility and Cytotoxicity against MC3T3-E1

Fabrication of reinforced scaffolds to repair and regenerate defected bone is still a major challenge. Bone tissue engineering is an advanced medical strategy to restore or regenerate damaged bone. The excellent biocompatibility and osteogenesis behavior of porous scaffolds play a critical role in bone regeneration. In current studies, we synthesized polymeric nanocomposite material through free-radical polymerization to fabricate porous nanocomposite scaffolds by freeze drying. Functional group, surface morphology, porosity, pore size, and mechanical strength were examined through Fourier Transform Infrared Spectroscopy (FTIR), Single-Electron Microscopy (SEM), Brunauer-Emmet-Teller (BET), and Universal Testing Machine (UTM), respectively. These nanocomposites exhibit enhanced compressive strength (from 4.1 to 16.90 MPa), Young’s modulus (from 13.27 to 29.65 MPa) with well appropriate porosity and pore size (from 63.72 ± 1.9 to 45.75 ± 6.7 µm), and a foam-like morphology. The increasing amount of graphene oxide (GO) regulates the porosity and mechanical behavior of the nanocomposite scaffolds. The loading and sustained release of silver-sulfadiazine was observed to be 90.6% after 260 min. The in-vitro analysis was performed using mouse pre-osteoblast (MC3T3-E1) cell lines. The developed nanocomposite scaffolds exhibited excellent biocompatibility. Based on the results, we propose these novel nanocomposites can serve as potential future biomaterials to repair defected bone with the load-bearing application, and in bone tissue engineering.

A simple reaction-diffusion model for initial stages of biofouling in reverse osmosis membranes

Biofouling is a critical issue in membrane water and wastewater treatment as it greatly compromises the efficiency of the treatment processes and consequently increases operational and maintenance costs. It is difficult to control this operational challenge, so the development of effective biofouling monitoring and control methods and strategies is a critical issue for membrane technology and applications. In this work, we develop a simulation approach for evaluating the operational time of reverse osmosis (RO) membranes based on a reaction-diffusion (RD) type of model. This approach would help to understand different factors involved in the formation of biofilms including microbial population dynamics (replication and death rates of microbial cells) and nutrient consumption. The model is focused on the initial stages of the membrane biofouling that is initiated by attachment of microbial species to the membrane leading to pore blocking followed by the formation of thick cake layer. We applied this approach to study the RO membrane biofouling by Picochlorum algae, the most common biofouling agent in the seawater of the Arabian Gulf, at known contents of total organic carbon and essential nutrients. We found that the biofilm growth dynamics on an RO membrane is mainly defined by the ratio of the replication and death rates of microbial cells. The proposed approach should be useful for fast evaluation of the RO membrane performance in different environmental conditions without using significant computational resources. This methodology allows generalization for multi-microbial and multi-nutrient systems. The establishment of effective fouling control strategies should decrease operational and maintenance costs of RO membrane systems.

Electrochemical Behavior of Ti6Al4V Alloy Used in Dental Implants Immersed in Streptococcus gordonii and Fusobacterium nucleatum Solutions

The titanium alloy, Ti6Al4V, is used in dentistry for dental implants because of its excellent resistance to corrosion and its high biocompatibility. However, periimplantitis is considered the main reason for treatment failure. The Ti6Al4V alloy was used to study the corrosion behavior for dental implant applications, using an experimental arrangement of three electrodes with the bacteria Streptococcus gordonii and Fusobacterium nucleatum, in addition to Ringer's lactate as electrolytes, at 37 °C and a pH of 5.6. Their electrochemical behavior was studied by open circuit potential (OCP) and cyclic potentiodynamic polarization (CPP) according to ASTM G3-14 and ASTM G61-11, respectively. Scanning electron microscopy (SEM) was employed to determine the morphology of the alloy studied. An experimental model, in situ, was established with the bacteria present in an oral environment to understand the electrochemical behavior of the alloy used in dental implants. The greatest corrosion in Ti6Al4V alloy was produced by the medium that contained the bacterium Streptococcus gordonii, which is considered a primary colonizer. In addition, the Ti6Al4V alloy presented uniform corrosion in the three solutions at the different exposure times showing a negative hysteresis in CPP.

A Microbial Screening in Silico Method for the Fitness Step Evaluation in Evolutionary Algorithms

One of the most delicate stages of an evolutionary algorithm is the evaluation of the goodness of the solutions by some procedure providing a fitness value. However, although there are general rules, it is not always easy to find an appropriate evaluation function for a given problem. In the biological realm, today, there is a variety of experimental methods under the name of microbial screening to identify and select bacteria from their traits, as well as to obtain their fitness. In this paper, we show how given an optimization problem, a colony of synthetic bacteria or bacterial agents is able to evaluate the fitness of candidate solutions by building an evaluation function. The evaluation function is obtained simulating, in silico, a bacterial colony conducting the laboratory methods used in microbiology, biotechnology and synthetic biology to measure microbial fitness. Once the evaluation function is built, it is included in the code of the genetic algorithm as part of the fitness routine. The practical use of this approach is illustrated in two classic optimization problems. In silico routines have been programmed in Gro, a cell programming language oriented to synthetic biology, and can easily be customized to many other optimization problems.

Extraction of recombinant periplasmic proteins under industrially relevant process conditions: Selectivity and yield strongly depend on protein titer and methodology

In this work, we attempted to identify a method for the selective extraction of periplasmic endogenously expressed proteins, which is applicable at an industrial scale. For this purpose, we used an expression model that allows coexpression of two fluorescent proteins, each of which is specifically targeted to either the cytoplasm or periplasm. We assessed a number of scalable lysis methods (high‐pressure homogenization, osmotic shock procedures, extraction with ethylenediaminetetraacetic acid, and extraction with deoxycholate) for the ability to selectively extract periplasmic proteins rather than cytoplasmic proteins. Our main conclusion was that although we identified industrially scalable lysis conditions that significantly increased the starting purity for further purification, none of the tested conditions were selective for periplasmic protein over cytoplasmic protein. Furthermore, we demonstrated that efficient extraction of the expressed recombinant proteins was largely dependent on the overall protein concentration in the cell.