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In this paper, we mainly investigate the dynamics of traveling wavefronts for a model describing host tissue degradation by bacteria. We first establish the existence of spreading speed, and show that the spreading speed coincides with the minimal wave speed of traveling wavefronts. Moreover, a lower bound estimate of the spreading speed is given. Then, we prove that the traveling wavefronts with large speeds are globally exponentially stable, when the initial perturbation around the traveling wavefronts decays exponentially as x → − ∞ , but the initial perturbation can be arbitrarily large in other locations. The adopted methods are the weighted energy and the squeezing technique. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear mathematical model is proposed and analyzed to study the role of dissolved oxygen (DO)-dependent bacteria on biodegradation of one or two organic pollutant(s) in a water body. In the case of two organic pollutant(s), it is assumed that the one is fast degrading and the other is slow degrading and both are discharged into the water body from outside with constant rates. The density of bacteria is assumed to follow logistic model and its growth increases due to biodegradation of one or two organic pollutant(s) as well as with the increase in the concentration of DO. The model is analyzed using the stability theory of differential equations and by simulation. The model analysis shows that the concentration(s) of one or both organic pollutant(s) decrease(s) as the density of bacteria increases. It is noted that for very large density of bacteria, the organic pollutant(s) may be removed almost completely from the water body. It is found that simulation analysis confirms the analytical results. The results obtained in this paper are in line with the experimental observations published in literature. [ABSTRACT FROM AUTHOR]

Various bacteria are able to infect human organisms to induce less or more dangerous diseases. In response to them, the human immune system is usually activated. In addition, medical therapies to the patients can be applied. One of the most popular approaches is the use of various antibiotics. However, some bacteria are able to develop resistance against the applied antibiotics. Various approaches to study these phenomena are proposed in the literature, among them tools for big data analysis, machine learning, mathematical modeling, etc. In our paper, we consider a mathematical model describing the interactions between susceptible uninfected cells, infected cells, immune cells and bacteria. We study the properties of the model. We propose numerical scheme for obtaining the approximate solutions to the model system for various values of parameters and initial conditions. [ABSTRACT FROM AUTHOR]

In this paper, the asymptotical behavior of a chemostat model for E. coli and the virulent phage T4 is analyzed. The basic reproduction number R0 is proved to be a threshold which determines the outcome of the virulent phage T4. If R0 < 1, the virus dies out; if R0 > 1, the virus persists. Sufficient conditions for the Hopf bifurcation are also established. The theoretical results show that increasing the input of nutrient will result in an increase in the equilibrium population density of the virulent bacteriophage T4, but will have no effect on the equilibrium population density of E. coli. The results also show that increasing the input of nutrient or increasing the average lytic time for the infected E. coli can destabilize the interaction between E. coli and T4. [ABSTRACT FROM AUTHOR]

We discuss velocity-jump models for Chemotaxis of bacteria with an internal state that allows the velocity-jump rate to depend on the memory of the chemoattractant concentration along their path of motion. Using probabilistic techniques, we provide a pathwise result that shows that the considered process converges to an advection-diffusion process in the (long-time) diffusion limit. We also (re-)prove using the same approach that the same limiting equation arises for a related, simpler process with direct sensing of the chemoattractant gradient. Additionally, we propose a time discretization technique that retains these diffusion limits exactly, i.e. without error that depends on the time discretization. In the companion paper, these results are used to construct a coupling technique that allows numerical simulation of the process with internal state with asymptotic variance reduction, in the sense that the variance vanishes in the diffusion limit. [ABSTRACT FROM AUTHOR]

Identifying promoters is the key to understanding gene expression in bacteria. Promoters lie in tightly constrained positions relative to the transcription start site (TSS). In this paper, we address the problem of predicting transcription start sites in Escherichia coli. Knowing the TSS position, one can then predict the promoter position to within a few base pairs, and vice versa. The accepted method for promoter prediction is to use a pair of position weight matrices (PWMs), which define conserved motifs at the sigma-factor binding site. However this method is known to result in a large number of false positive predictions, thereby limiting its usefulness to the experimental biologist. We adopt an alternative approach based on the Support Vector Machine (SVM) using a modified mismatch spectrum kernel. Our modifications involve tagging the motifs with their location, and selectively pruning the feature set. We quantify the performance of several SVM models and a PWM model using a performance metric of area under the detection-error tradeoff (DET) curve. SVM models are shown to outperform the PWM on a biologically realistic TSS prediction task. We also describe a more broadly applicable peak scoring technique which reduces the number of false positive predictions, greatly enhancing the utility of our results. [ABSTRACT FROM AUTHOR]

A chaotic system can be used to transform a periodic input sequence of events, e.g. impulses, into a sequence of output events. Even after transient, the output sequence is often aperiodic. In particular, it might happen that the output events are basically synchronized with the input events, but that some of them are randomly skipped from the output time series (imperfect phase synchronization [Zacks et al., 1999, 2000]). This phenomenon has been neatly observed by Schimz and Hildebrand [1992] in a rich series of experiments on the locomotor behavior of Halobacterium salinarium, where the input event was a light impulse and the output event was the reversal in the swimming direction of the bacterium. In this paper, we show that the same phenomenon occurs when classical, low dimensional chaotic oscillators are forced by a periodic sequence of impulses. This proves, on one side, that imperfect phase synchronization is a common phenomenon in chaotic oscillators subjected to periodic sequences of impulses, and, on the other side, that there are high chances that the locomotor behavior of Halobacterium salinarium can be modeled by a low dimensional deterministic model. [ABSTRACT FROM AUTHOR]

Genomic islands (GIs) are clusters of functionally related genes acquired by lateral genetic transfer (LGT), and they are present in many bacterial genomes. GIs are extremely important for bacterial research, because they not only promote genome evolution but also contain genes that enhance adaption and enable antibiotic resistance. Many methods have been proposed to predict GI. But most of them rely on either annotations or comparisons with other closely related genomes. Hence these methods cannot be easily applied to new genomes. As the number of newly sequenced bacterial genomes rapidly increases, there is a need for methods to detect GI based solely on sequences of a single genome. In this paper, we propose a novel method, GI-SVM, to predict GIs given only the unannotated genome sequence. GI-SVM is based on one-class support vector machine (SVM), utilizing composition bias in terms of k-mer content. From our evaluations on three real genomes, GI-SVM can achieve higher recall compared with current methods, without much loss of precision. Besides, GI-SVM allows flexible parameter tuning to get optimal results for each genome. In short, GI-SVM provides a more sensitive method for researchers interested in a first-pass detection of GI in newly sequenced genomes. [ABSTRACT FROM AUTHOR]

We discuss variance reduced simulations for an individual-based model of chemotaxis of bacteria with internal dynamics. The variance reduction is achieved via a coupling of this model with a simpler process in which the internal dynamics has been replaced by a direct gradient sensing of the chemoattractants concentrations. In the companion paper ["Individual-based models for bacterial chemotaxis in the diffusion limit" (to appear in Math. Models Methods Appl. Sci., DOI: 10.1142/S0218202513500243)], we have rigorously shown, using a pathwise probabilistic technique, that both processes converge towards the same advection-diffusion process in the diffusive asymptotics. In this work, a direct coupling is achieved between paths of individual bacteria simulated by both models, by using the same sets of random numbers in both simulations. This coupling is used to construct a hybrid scheme with reduced variance. We first compute a deterministic solution of the kinetic density description of the direct gradient sensing model; the deviations due to the presence of internal dynamics are then evaluated via the coupled individual-based simulations. We show that the resulting variance reduction is asymptotic, in the sense that, in the diffusive asymptotics, the difference between the two processes has a variance which vanishes according to the small parameter. [ABSTRACT FROM AUTHOR]

The traditional method for controlling pests is the application of chemical pesticides. Growing concern on the negative effects of chemicals has encouraged the development of alternatives. Inundatively and inoculatively applied microbial control agents (virus, bacteria, fungi, and entomopathogenic nematodes) have been developed as alternative control methods of a wide variety of pests. A mathematical model for microbial control of pests is formulated in this paper. The dynamical characteristics of the system are studied. The role of time-delay has been discussed. Numerical simulations are carried out to illustrate the analytical findings. Biological implications have been discussed. [ABSTRACT FROM AUTHOR]

There is a widely shared and potentially well-justified enthusiasm for autonomous field-deployed (FD) wearable, implantable, and environmental sensors for the continuous monitoring of a variety of chronic conditions, such as diabetes, depression, irritable bowel syndrome, and soil nitrate depletion. These FD sensors are often viewed as miniaturized versions of laboratory-based or point-of-care (POC) biosensors, with the primary focus being on material development and mechanical form factor challenges (e.g., stretchability, flexibility, and biocompatibility). In this article, we highlight that the FD sensors are fundamentally different compared to lab-based or POC sensors. We borrow concepts from biology (e.g., bacteria) to quantify the fundamental challenges inherent to such sensors and strategies to overcome them. [ABSTRACT FROM AUTHOR]

In this study, eugenol-loaded mPEG-PCL nanoparticles were used to improve the anti-bacterial properties of eugenol in an attempt to eliminate the resistant bacteria. The mPEG-PCL copolymer was prepared by ring-opening polymerization of ε -caprolactone monomer in the vicinity of a dry mPEG and a tin (II) octoate catalyst. Polymeric nanoparticles were prepared through the nanoprecipitation procedure. The particle size and zeta potential of mPEG-PCL/eugenol were found to be 1 5 7. 2 3 ± 3. 8 1 nm and − 6. 9 5 ± 0. 1 9 mV, respectively. The polymeric nanoparticle structure was identified by AFM, FT-IR, and DSC techniques. To evaluate and compare the antibacterial efficiency of mPEG-PCL/eugenol with that of free eugenol, a turbidity assay was used in association with gram-positive and gram-negative bacteria. SEM images were taken from the bacteria before and after exposure to the mPEG-PCL/eugenol. The colony-forming unit per milliliter (CFU/mL) method was used to evaluate the performance of mPEG-PCL/eugenol on the growth rate of bacteria in hospital wastewater. The results showed that the mPEG-PCL/eugenol nanoparticles demonstrated an enormous antibacterial effect in connection with wild gram-negative bacteria strains at 40 μ M concentration and 37∘C. In the original hospital wastewater, mPEG-PCL/eugenol at the concentration of 0.125 μ M at 25∘C showed the largest decrease in the total microbial count. Nanotechnology is very effective in eliminating bacterial infections and can be considered as a suitable alternative to antibiotics. In this research, the antibacterial effect of eugenol entrapped in polymeric nanoparticles (mPEG-PCL/eugenol) on resistant bacteria was investigated. mPEG-PCL copolymer was used as a carrier to prepare nano micelles of eugenol. Then, the antibacterial effect of eugenol-loaded mPEG-PCL on drug resistant bacteria isolated from hospital wastewater was studied. [ABSTRACT FROM AUTHOR]

The use of engineered antigen carriers to optimize the immune response to recombinant subunit vaccines has seen great advances in recent years. Optimization can take several forms, such as facilitating stimulation of certain immune cells or amplifying the adjuvancy effect of the vaccine formulation. In this paper, we applied dose/response analysis to demonstrate the ability of outer membrane vesicle (OMV) antigen carriers derived from engineered Escherichia coli to produce strong antigen-specific immune responses to a model antigen at a significantly decreased antigen load compared to an industry standard alum-based control. Inflammopathology and histological analysis of extended studies further supported a capacity to enhance immune cell recruitment locally at the injection site while decreasing inflammation and eliminating injection site scaring. The results indicate a strong potential for OMV-based vaccines as recombinant antigen delivery vehicles, affording strong immunogenicity at low doses with a broadly applicable platform for recombinant subunit antigen inclusion. [ABSTRACT FROM AUTHOR]

Cholera is a serious threat to the health of human-kind all over the world and its control is a problem of great concern. In this context, a nonlinear mathematical model to control the prevalence of cholera disease is proposed and analyzed by incorporating TV and social media advertisements as a dynamic variable. It is considered that TV and social media ads propagate the knowledge among the people regarding the severe effects of cholera disease on human health along with its precautionary measures. It is also assumed that the mode of transmission of cholera disease among susceptible individuals is due to consumption of contaminated drinking water containing it Vibrio cholerae. Moreover, the propagation of knowledge through TV and social media ads makes the people aware to adopt precautionary measures and also the aware people make some effectual efforts to washout the bacteria from the aquatic environment. Model analysis reveals that increase in the washout rate of bacteria due to aware individuals causes the stability switch. It is found that TV and social media ads have the potential to reduce the number of infectives in the region and thus control the cholera epidemic. Numerical simulation is performed for a particular set of parameter values to support the analytical findings. [ABSTRACT FROM AUTHOR]

The growth trend of publications in the field of nanoparticles biosynthesis by bacteria was analyzed using bibliometric techniques to the identification of the areas with significant development and the orientations that have guided the research on bacteria. This study extracted data from the Clarivate Analytics Web of Science (WoS) and Scopus between 2000 and 2020 to compare results. The number of articles published annually, participating countries, resource growth rate, most used keywords and research collaborations were obtained from bibliometric analysis. The results showed that nanoparticle documents in materials science, biochemistry, genetics and molecular biology have improved citation rates as the authors researched in multidisciplinary areas. Although these keywords have the most sites, they are not emerging keywords, and their most common use was in the years 2014–2018. The results showed the upward trend of articles published from 2000 to 2020, most of which were related to the last 10 years. The 5 countries that had the most articles published in this field were China, USA, India, Germany and Iran. The top sources that had the most published documents in this field had a similar scope to our research. The results of each section had a significant relationship with other sections of this study. VOS viewer program was used for quantitative analysis. It seems that bibliometric methods will complement meta-analysis and qualitative structured literature reviews as a method for reviewing and evaluating scientific literature. The advantage of the bibliographic analysis was the awareness of trends in a study area. Documents by subject area of Nanoparticle Biosynthesis by Bacteria that related to material science. [ABSTRACT FROM AUTHOR]

No abstract received. [ABSTRACT FROM AUTHOR]

Recently a new method, SEnsing of Phage-Triggered Ion Cascade (SEPTIC) was proposed for the rapid detection and identification of bacteria via the electrical field caused by the stochastic emission of ions during phage infection. In this Letter, we present linear network theoretical considerations about the detection limits of the method. The considerations are based on our published data of the E. coli detection experiments and on the assumption of a linear response between the number of bacteria and the measured power density spectrum of the fluctuation-signal. Some practical limits of the detectability of the present agents with possible noise measurement arrangements are discussed in this paper. The calculations indicate that the detection and identification of a single bacterium can be achieved with natural (wild) phages with reasonable efforts within a time window of 10 minutes. [ABSTRACT FROM AUTHOR]

Bacterial plasmids play a fundamental role in antibiotic resistance. However, a lack of knowledge about their biology is an obstacle in fully understanding the mechanisms and properties of plasmid-mediated resistance. This has motivated investigations of real systems in vitro to analyze the transfer and replication of plasmids. In this work, we address this issue with mathematical modeling. We formulate and perform a qualitative analysis of a nonlinear system of ordinary differential equations describing the competition dynamics between plasmids and sensitive and resistant bacteria. In addition, we estimated parameter values from empirical data. Our model predicts scenarios consistent with biological phenomena. The elimination or spread of infection depends on factors associated with bacterial reproduction and the transfer and replication of plasmids. From the estimated parameters, three bacterial growth experiments were analyzed in vitro. We determined the experiment with the highest bacterial growth rate and the highest rate of plasmid transfer. Moreover, numerical simulations were performed to predict bacterial growth. [ABSTRACT FROM AUTHOR]

We prove that the numerical invariant 3 μ − 4 τ of a reduced irreducible plane curve singularity germ is non-negative, non-decreasing under blowups and strictly increasing unless the curve is non-singular. This provides a new perspective to understand the question posed by Dimca and Greuel. Moreover, our work can be put in the general framework of discovering monotonic invariants under blowups. [ABSTRACT FROM AUTHOR]

Prokaryote adaptive immunity (CRISPR-Cas systems) can be a threat to its carriers. We analyze the risks of autoimmune reactions related to adaptive immunity in prokaryotes by computational methods. We found important differences between bacteria and archaea with respect to autoimmunity potential. According to the results of our analysis, CRISPR-Cas systems in bacteria are more prone to self-targeting even though they possess fewer spacers per organism on average than archaea. The results of our study provide opportunities to use self-targeting in prokaryotes for biological and medical applications. [ABSTRACT FROM AUTHOR]

Uniform representation of semigroups is introduced. It is proved that any uniform representation of an ample semigroup can be expressed as the direct sum of some representations obtained via homogenous representations on primitive adequate semigroups. Also, we give the structure of homogenous representations of primitive adequate semigroups. In addition, we consider indecomposable uniform representations of ample semigroups and their constructions. [ABSTRACT FROM AUTHOR]

Based on previous studies, empirical distribution of the bacterial burst size varies even in a population of isogenic bacteria. Since bacteriophage progenies increase linearly with time, it is the lysis time variation that results in the bacterial burst size variations. Here, the burst size variation is computationally modeled by considering the lysis time decisions as a game. Each player in the game is a bacteriophage that has initially infected and lysed its host bacterium. Also, the payoff of each burst size strategy is the average number of bacteria that are solely infected by the bacteriophage progenies after lysis. For calculating the payoffs, a new version of ball and bin model with time dependent occupation probabilities (TDOP) is proposed. We show that Nash equilibrium occurs for a range of mixed burst size strategies that are chosen and played by bacteriophages, stochastically. Moreover, it is concluded that the burst size variations arise from choosing mixed lysis strategies by each player. By choosing the lysis time and also the burst size stochastically, the released bacteriophage progenies infect a portion of host bacteria in environment and avoid extinction. The probability distribution of the mixed burst size strategies is also identified. [ABSTRACT FROM AUTHOR]

Pathogenic bacteria in human system mature through the bio-synthesis of protective layer known as cell wall. This bacterial cell wall growth occurs in the presence of enzyme released by it. After maturation by the cell wall formation, pathogenic bacteria become harmful for human body as they are responsible for different diseases. Antibiotics or drugs are employed for curing bacterial diseases through the inhibition of this maturation process and it occurs by the binding progression of antibiotics with the released enzyme. But nowadays, drugs or antibiotics like -lactum family (Amoxcillin) which are generally used for inhibition of bio-synthesis of cell wall become ineffective due to evolution of antibiotic resistance by the bacteria. Antibiotic resistance occurs when an antibiotic has lost its ability to effectively control or kill bacterial growth. As a result, the bacteria becomes 'resistant' and continue to multiply for the generation of robust pathogenic bacteria in spite of drug administration. This is due to the release of another type of enzyme by the resistant bacteria which binds with the active antibiotic or drug making it ineffective. Hence, another type of drug (Clauvanic acid) is combined to resist the activity of drug hydrolyzing enzyme so that the initial drug can act effectively. Hence a combination of drug therapy is applied to cure the bacterial diseases successfully. We developed a mathematical model based on the bacterial enzyme and bacterial cell wall proliferation mechanism and showed how we can reduce the bacterial infection in the resistant cases with application of combination drugs (Amoxcillin and Clauvanic acid) to restore normal health. Based on the enzymatic activity and individual drug dynamics we studied the overall system under the single drug and combinational drug administration through our formulated model analysis. We also demonstrated the different dosing time interval and dosing concentration to evaluate the optimized drug administration for arresting the cell wall formation completely. Sensitivity of the different kinetic rate constant also has been performed with subject to drug hydrolyzing enzyme. Our analytical and numerical studies also confirm the efficiency of the combinational drug treatment compared to single drug treatment being more effective in drug resistant cases providing recovery from bacterial disease. [ABSTRACT FROM AUTHOR]

Mathematical models can be very useful in determining efficient and successful antibiotic dosing techniques against bacterial infections. There are several challenging issues involved, the presence of drug resistant bacteria being one. Recent rise in antibiotic resistant strains of bacteria is a grave public health hazard, hence there is a need to develop dosing protocols taking into account the presence of these resistant strains. In this study, we consider a model for antibiotic treatment of a bacterial infection where the bacteria are divided into two sub-populations: susceptible and resistant. The mechanism of acquisition of resistance by the susceptible bacteria considered is via the process of conjugation. We find the steady-state solutions under an antibiotic protocol of discrete periodic doses and analyze their stability. We also prove an extension of a result that pertains to the persistence of bacteria. In addition, we perform the bifurcation analysis under this dosing protocol and show that bi-stability exists for the bacterial population. Furthermore, efficient treatment strategies are devised that ensure bacterial elimination while minimizing the quantity of antibiotic used. Such treatments are necessary to decrease the chances of further development of resistance in bacteria and to minimize the overall treatment cost. We consider the cases of varying antibiotic costs, different initial bacterial densities and bacterial attachment to solid surfaces, and obtain the optimal strategies for all the cases. The results show that the optimal treatments ensure disinfection for a wide range of scenarios. [ABSTRACT FROM AUTHOR]

Effects of weak magnetic fields are observed on the growth of various bacterial strains. Different sources of a constant magnetic field are used to demonstrate that ion transport in the nutrient broth and bacterial cellular dynamics is perturbed in the presence of weak magnetic field which affects the mobility and absorption of nutrients in cells and hence their doubling rate. The change is obvious after a few hours of exposure and keeps on increasing with time for all the observed species. The growth rate depends on the field strength and the nature of the magnetic field. The field effect varies with the shape and the structure of the bacterial cell wall as well as the concentration of nutrient broth. We closely study the growth of three species Escherichia coli, Pseudomonas aeruginosa and Staphylococcus epidermidis with the same initial concentrations at the same temperature in the same laboratory environment. Our results indicate that the weak static field of a few gauss after a few hours gives a measurable change in the growth rates of all bacterial species. This shows that the same magnetic field has different effects on different species in the same environment. [ABSTRACT FROM AUTHOR]

Several sources of water pollution are causing negative consequences to marine life. The organisms that are more affected are fishes and marine mammals since they are at the top of the food chain. They are directly exposed to high levels of toxins in water and/or they feed on other fishes that are contaminated. Unfortunately, the main cause of the contaminations, and thus of the fish deaths, come from human activities, such as industry, agriculture, municipal wastewater and solid wastes. The present study is concerned with the effect of organic and inorganic pollutants on the survival of fish in water bodies. We introduce a nonlinear mathematical model by considering five interacting variables; organic pollutants, inorganic pollutants, bacteria, dissolved oxygen and fish in the water body. The model is analyzed using the stability theory of differential equations and to confirm the analytical findings, numerical simulations are performed. Our results suggest that to maintain water quality and to save fish life, the global community has to limit the release of organic and inorganic pollutants into the aquatic system. [ABSTRACT FROM AUTHOR]

Silver particles show antibacterial and antiseptic properties at the nanoscale. Such properties result from an alteration in the binding capacity of silver atoms in bits of less than 6.5nm which enables them to kill harmful organisms. Silver nanoparticles are now the most broadly used agents in the area of nanotechnology after carbon nanotubes. Given that currency bills are one of the major sources of bacterial disseminations and their contamination has recently been nominated as a critical factor in gastrointestinal infections and possibly colon cancers, here we propose a new method for producing antibacterial bank notes by using silver nanoparticles. Older bank notes are sprayed with acetone to clean the surface. The bank note is put into a petri-dish containing a solution of silver nitrate and ammonia so that it is impregnated. The bank notes are then reduced with the formaldehyde gas, which penetrates its texture and produces silver nanoparticles in the cellulose matrix. The side products of the reactions are quickly dried off and the procedure ends with the drying of the bank note. The transmission electron microscope (TEM) images confirmed the nanoscale size range for the formed particles while spectroscopy methods, such as XRD, provided proof for the metallic nature of the particles. Bacterial challenge tests then showed that no colonies of the three tested bacterium ( Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa survived on the sample after a 72h incubation period. This study has provided a method for synthesizing silver NPs directly into the texture of fabrics and textiles (like that of bank notes) which can result in lower production costs, making the use of silver NPs economically beneficial. The method, specifically works on the fabric of bank notes, suggesting a method to tackle the transmission of bacteria through bank notes. Moreover, this study is a testament to the strong antibacterial nature of even low concentrations of silver NPs. [ABSTRACT FROM AUTHOR]

Diversity of drugs against bacterial infections, and development of resistance to such drugs are increasing. We formulate and analyze a deterministic model for the population dynamics of sensitive and resistant bacteria to multiple bactericidal and bacteriostatic antibiotics, assuming that drug resistance is acquired through mutations and plasmid transmission. Model equilibria are determined from qualitative analysis, and numerical simulations are used to assess temporal dynamics of sensitive and drug-resistant bacteria. The model presents three possibilities: elimination of bacteria, persistence of only resistant bacteria, or coexistence of sensitive and resistant bacteria. Evolution to one of these scenarios depends on thresholds numbers involving sensitive and resistant bacteria. [ABSTRACT FROM AUTHOR]

We consider a model system for the collective behavior of oxygen-driven swimming bacteria in an aquatic fluid. In certain parameter regimes, such suspensions of bacteria feature large-scale convection patterns as a result of the hydrodynamic interaction between bacteria. The presented model consist of a parabolic–parabolic chemotaxis system for the oxygen concentration and the bacteria density coupled to an incompressible Stokes equation for the fluid driven by a gravitational force of the heavier bacteria. We show local existence of weak solutions in a bounded domain in ℝd, d = 2, 3 with no-flux boundary condition and in ℝ2 in the case of inhomogeneous Dirichlet conditions for the oxygen. [ABSTRACT FROM AUTHOR]

The complexity of DNA sequences is evaluated in order to differentiate between protein-coding and noncoding RNA segments. The method is based on computing the Shannon entropy of the sequences. By comparing the entropy of the original sequence with that of its shuffled one, we identify the source of the difference between the two segments and their relative contributions to the sequence. To demonstrate the method, the DNA sequences of the bacterium Clostridium difficile 630(G + C = 29.1%) and Bdellovibrio bacteriovorus(G + C = 50.6%) are analyzed, which are representatives of bacteria with unbalanced and balanced nucleotide content, respectively. It is shown that in both bacteria, regardless of nucleotide content, ΔrS — the relative difference of the two entropies — is significantly greater in protein-coding regions, when compared with noncoding RNA segments. [ABSTRACT FROM AUTHOR]

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment. [ABSTRACT FROM AUTHOR]

The soil bacterium Cupriavidus metallidurans CH34 resist selenite by reducing it into the insoluble and less toxic elemental selenium. Two mechanisms of reduction of selenium oxides in C. metallidurans CH34 were highlighted: assimilation leading to organic species and detoxification leading to precipitation of selenite in nanoparticules of elemental selenium. The alkyl selenide detected as an intermediate product during assimilation of selenite or as the major accumulated chemical form during assimilation of selenate was identified as selenomethionine. Soluble and membrane proteins were extracted from C. metallidurans CH34 submitted to selenium oxides challenge. After separation by SDS-PAGE, µPIXE analyses were used for Se identification and quantification at a micrometer scale. The profiles of Se distribution in the different samples suggest a non-specific incorporation of selenium probably reflecting the incorporation of selenomethionin in place of the naturally occurring methionin. [ABSTRACT FROM AUTHOR]