Bacterial outer membrane vesicles provide an alternative pathway for trafficking of Escherichia coli O157 type III secreted effectors to epithelial cells.

IMPORTANCE: Bacteria can package protein cargo into nanosized membrane blebs that are shed from the bacterial membrane and released into the environment. Here, we report that a type of pathogenic bacteria called enterohemorrhagic Escherichia coli O157 (EHEC) uses their membrane blebs (outer membrane vesicles) to package components of their type 3 secretion system and send them into host cells, where they can manipulate host signaling pathways including those involved in infection response, such as immunity. Usually, EHEC use a needle-like apparatus to inject these components into host cells, but packaging them into membrane blebs that get taken up by host cells is another way of delivery that can bypass the need for a functioning injection system.

Harnessing water fleas for water reclamation: A nature-based tertiary wastewater treatment technology.

Urbanisation, population growth, and climate change have put unprecedented pressure on water resources, leading to a global water crisis and the need for water reuse. However, water reuse is unsafe unless persistent chemical pollutants are removed from reclaimed water. State-of-the-art technologies for the reduction of persistent chemical pollutants in wastewater typically impose high operational and energy costs and potentially generate toxic by-products (e.g., bromate from ozonation). Nature-base solutions are preferred to these technologies for their lower environmental impact. However, so far, bio-based tertiary wastewater treatments have been inefficient for industrial-scale applications. Moreover, they often demand significant financial investment and large infrastructure, undermining sustainability objectives. Here, we present a scalable, low-cost, low-carbon, and retrofittable nature-inspired solution to remove persistent chemical pollutants (pharmaceutical, pesticides and industrial chemicals). We showed Daphnia's removal efficiency of individual chemicals and chemicals from wastewater at laboratory scale ranging between 50 % for PFOS and 90 % for diclofenac. We validated the removal efficiency of diclofenac at prototype scale, showing sustained performance over four weeks in outdoor seminatural conditions. A techno-commercial analysis on the Daphnia-based technology suggested several technical, commercial and sustainability advantages over established and emerging treatments at comparable removal efficiency, benchmarked on available data on individual chemicals. Further testing of the technology is underway in open flow environments holding real wastewater. The technology has the potential to improve the quality of wastewater effluent, meeting requirements to produce water appropriate for reuse in irrigation, industrial application, and household use. By preventing persistent chemicals from entering waterways, this technology has the potential to maximise the shift to clean growth, enabling water reuse, reducing resource depletion and preventing environmental pollution.

Silver-doped bioactive glass fibres as a potential treatment for wound-associated bacterial biofilms.

Chronic wounds are a drain on global health services and remain a major area of unmet clinical need. Chronic wounds are characterised by a stable and stubborn bacterial biofilm which hinders innate immune response and delays or prevents wound healing. Bioactive glass (BG) fibres offer a promising novel treatment for chronic wounds by targeting the wound-associated biofilm. In this study, the antimicrobial properties of silver-doped BG fibres were tested against Pseudomonas aeruginosa biofilms, which are commonly found in chronic wound infections. Results showed that BG fibres doped with silver resulted in a 5log10 reduction in biofilm formation whereas silver-free fibres only reduced formation by log10, therefore silver-doped fibres possess stronger antimicrobial effects. Moreover, there appeared to be a synergistic effect between the fibres and the silver as the application of the silver-doped fibres placed directly in contact with the forming biofilm resulted in a higher reduction in biofilm formation compared to treatments either: using the dissolution ions, using BG powder, or when the fibres were placed in an insert above the biofilm, inhibiting physical contact, instead. This suggests that the physical properties of the fibres, as well as silver, influence biofilm formation. Finally, results demonstrated that silver chloride, which is not antimicrobial, forms and the concentrations of antimicrobial silver species, namely silver ions and nanoparticles, reduce over time when fibres are soaked in cell culture media, which partially explains why the silver-doped dissolution ions contained lower antimicrobial activity compared to the fibres. As silver chloride is more likely to form with increased temperature and time, the antimicrobial activity of silver-containing dissolution ions is highly dependent on the length of ageing and storage conditions. Many studies investigate the antimicrobial and cytotoxic properties of biomaterials through their dissolution products. However, instability of antimicrobial silver species due to silver chloride formation and its effect on antimicrobial properties of silver-based biomaterials has not been reported before and could influence past and future dissolution-based assays as results showed that the antimicrobial activity of silver-based dissolution ions can vary greatly depending on post processing steps and can therefore produce misleading data.

Unravelling microbial efflux through mathematical modelling.

AbstractMathematical modelling is a useful tool that is increasingly used in the life sciences to understand and predict the behaviour of biological systems. This review looks at how this interdisciplinary approach has advanced our understanding of microbial efflux, the process by which microbes expel harmful substances. The discussion is largely in the context of antimicrobial resistance, but applications in synthetic biology are also touched upon. The goal of this paper is to spark further fruitful collaborations between modellers and experimentalists in the efflux community and beyond.

Mathematical Modelling Highlights the Potential for Genetic Manipulation as an Adjuvant to Counter Efflux-Mediated MDR in Salmonella.

Bacteria have developed resistance to antibiotics by various mechanisms, notable amongst these is the use of permeation barriers and the expulsion of antibiotics via efflux pumps. The resistance-nodulation-division (RND) family of efflux pumps is found in Gram-negative bacteria and a major contributor to multidrug resistance (MDR). In particular, Salmonella encodes five RND efflux pump systems: AcrAB, AcrAD, AcrEF, MdsAB and MdtAB which have different substrate ranges including many antibiotics. We produce a spatial partial differential equation (PDE) model governing the diffusion and efflux of antibiotic in Salmonella, via these RND efflux pumps. Using parameter fitting techniques on experimental data, we are able to establish the behaviour of multiple wild-type and efflux mutant Salmonella strains, which enables us to produce efflux profiles for each individual efflux pump system. By combining the model with a gene regulatory network (GRN) model of efflux regulation, we simulate how the bacteria respond to their environment. Finally, performing a parameter sensitivity analysis, we look into various different targets to inhibit the efflux pumps. The model provides an in silico framework with which to test these potential adjuvants to counter MDR.

Dynamic Boolean modelling reveals the influence of energy supply on bacterial efflux pump expression.

Antimicrobial resistance (AMR) is a global health issue. One key factor contributing to AMR is the ability of bacteria to export drugs through efflux pumps, which relies on the ATP-dependent expression and interaction of several controlling genes. Recent studies have shown that significant cell-to-cell ATP variability exists within clonal bacterial populations, but the contribution of intrinsic cell-to-cell ATP heterogeneity is generally overlooked in understanding efflux pumps. Here, we consider how ATP variability influences gene regulatory networks controlling expression of efflux pump genes in two bacterial species. We develop and apply a generalizable Boolean modelling framework, developed to incorporate the dependence of gene expression dynamics on available cellular energy supply. Theoretical results show that differences in energy availability can cause pronounced downstream heterogeneity in efflux gene expression. Cells with higher energy availability have a superior response to stressors. Furthermore, in the absence of stress, model bacteria develop heterogeneous pulses of efflux pump gene expression which contribute to a sustained sub-population of cells with increased efflux expression activity, potentially conferring a continuous pool of intrinsically resistant bacteria. This modelling approach thus reveals an important source of heterogeneity in cell responses to antimicrobials and sheds light on potentially targetable aspects of efflux pump-related antimicrobial resistance.

Biofilm viability checker: An open-source tool for automated biofilm viability analysis from confocal microscopy images.

Quantifying biofilm formation on surfaces is challenging because traditional microbiological methods, such as total colony-forming units (CFUs), often rely on manual counting. These are laborious, resource intensive techniques, more susceptible to human error. Confocal laser scanning microscopy (CLSM) is a high-resolution technique that allows 3D visualisation of biofilm architecture. In combination with a live/dead stain, it can be used to quantify biofilm viability on both transparent and opaque surfaces. However, there is little consensus on the appropriate methodology to apply in confocal micrograph processing. In this study, we report the development of an image analysis approach to repeatably quantify biofilm viability and surface coverage. We also demonstrate its use for a range of bacterial species and translational applications. This protocol has been created with ease of use and accessibility in mind, to enable researchers who do not specialise in computational techniques to be confident in applying these methods to analyse biofilm micrographs. Furthermore, the simplicity of the method enables the user to adapt it for their bespoke needs. Validation experiments demonstrate the automated analysis is robust and accurate across a range of bacterial species and an improvement on traditional microbiological analysis. Furthermore, application to translational case studies show the automated method is a reliable measurement of biomass and cell viability. This approach will ensure image analysis is an accessible option for those in the microbiology and biomaterials field, improve current detection approaches and ultimately support the development of novel strategies for preventing biofilm formation by ensuring comparability across studies.

Time dependent asymptotic analysis of the gene regulatory network of the AcrAB-TolC efflux pump system in gram-negative bacteria.

Efflux pumps are a mechanism of intrinsic and evolved resistance in bacteria. If an efflux pump can expel an antibiotic so that its concentration within the cell is below a killing threshold the bacteria are resistant to the antibiotic. Efflux pumps may be specific or they may pump various different substances. This is why many efflux pumps confer multi drug resistance (MDR). In particular over expression of the AcrAB-TolC efflux pump system confers MDR in both Salmonella and Escherichia coli. We consider the complex gene regulation network that controls expression of genes central to controlling the efflux associated genes acrAB and acrEF in Salmonella. We present the first mathematical model of this gene regulatory network in the form of a system of ordinary differential equations. Using a time dependent asymptotic analysis, we examine in detail the behaviour of the efflux system on various different timescales. Asymptotic approximations of the steady states provide an analytical comparison of targets for efflux inhibition.

An updated systematic review and meta-analysis on efficacy of Sofosbuvir in treating hepatitis C-infected patients with advanced chronic kidney disease.

Sofosbuvir seems to be a revolutionary treatment for Hepatitis C-infected patients with advanced chronic kidney disease (CKD) but existing evidence is not quite adequate. The aim of this study was to evaluate the efficacy and safety of Sofosbuvir-based therapy without Ribavirin for all hepatitis C virus genotypes among patients with advanced CKD. We conducted an updated systematic literature search from the beginning of 2013 up to June 2020. Sustained virologic response (SVR) rate at 12 and/or 24 weeks after the end of treatment, and adverse events in HCV-infected patients with advanced CKD were pooled using random effects models. We included 27 published articles in our meta-analyses, totaling 1,464 HCV-infected patients with advanced CKD. We found a substantial heterogeneity based on the I2 index (P = 0.00, I2 = 56.1%). The pooled SVR rates at 12 and 24 weeks after the end of Sofosbuvir-based treatment were 97% (95% Confidence Interval: 95-99) and 95% (89-99) respectively. The pooled SVR12 rates were 98% (96-100) and 94% (90-97) in patients under 60 and over 60 years old respectively. The pooled incidence of severe adverse events was 0.11 (0.04-0.19). The pooled SVR12 rate after completion of the half dose regimen was as high as the full dose treatment but it was associated with less adverse events (0.06 versus 0.14). The pooled SVR12 rate was 98% (91-100) in cirrhotic patients and 100% (98-100) in non-cirrhotic patients. The endorsement of Sofosbuvir-based regimen can improve the treatment of hepatitis C virus infection in patients with advanced CKD.

A review of co-culture models to study the oral microenvironment and disease.

Co-cultures allow for the study of cell-cell interactions between different eukaryotic species or with bacteria. Such an approach has enabled researchers to more closely mimic complex tissue structures. This review is focused on co-culture systems modelling the oral cavity, which have been used to evaluate this unique cellular environment and understand disease progression. Over time, these systems have developed significantly from simple 2D eukaryotic cultures and planktonic bacteria to more complex 3D tissue engineered structures and biofilms. Careful selection and design of the co-culture along with critical parameters, such as seeding density and choice of analysis method, have resulted in several advances. This review provides a comparison of existing co-culture systems for the oral environment, with emphasis on progression of 3D models and the opportunity to harness techniques from other fields to improve current methods. While filling a gap in navigating this literature, this review ultimately supports the development of this vital technique in the field of oral biology.

The combination of sofosbuvir and daclatasvir is effective and safe in treating patients with hepatitis C and severe renal impairment.

BACKGROUND AND AIM: Many of the treatment regimens available for hepatitis C include sofosbuvir. Unfortunately, sofosbuvir has not been recommended for use in patients with severe renal impairment leaving these group of patients with very few options. Nevertheless, there are many reports in which these patients have been treated with sofosbuvir-containing regiments without important adverse events. This study aims at determining the safety and effectiveness of a sofosbuvir-based treatment in patients with severe renal impairment, including those on hemodialysis. METHOD: We enrolled subjects with hepatitis C and estimated glomerular filtration rate under ml/min/1.73m2 from 13 centers in Iran. Patients were treated for 12 weeks with a single daily pill containing 400-mg sofosbuvir and 60-mg daclatasvir. Patients with cirrhosis were treated for 24 weeks. Response to treatment was evaluated 12 weeks after end of treatment (sustained viral response [SVR]). ClinicalTrials.gov identifier: NCT03063879. RESULTS: A total of 103 patients were enrolled from 13 centers. Seventy-five patients were on hemodialysis. Thirty-nine had cirrhosis and eight were decompensated. Fifty-three were Genotype 1, and 27 Genotype 3. Twenty-seven patients had history of previous failed interferon-based treatment. Three patients died in which cause of death was not related to treatment. Six patients were lost to follow-up. The remaining 94 patients all achieved SVR. No adverse events leading to discontinuation of medicine was observed. CONCLUSIONS: The combination of sofosbuvir and daclatasvir is an effective and safe treatment for patients infected with all genotypes of hepatitis C who have severe renal impairment, including patients on hemodialysis.

Intracellular Energy Variability Modulates Cellular Decision-Making Capacity.

Cells generate phenotypic diversity both during development and in response to stressful and changing environments, aiding survival. Functionally vital cell fate decisions from a range of phenotypic choices are made by regulatory networks, the dynamics of which rely on gene expression and hence depend on the cellular energy budget (and particularly ATP levels). However, despite pronounced cell-to-cell ATP differences observed across biological systems, the influence of energy availability on regulatory network dynamics is often overlooked as a cellular decision-making modulator, limiting our knowledge of how energy budgets affect cell behaviour. Here, we consider a mathematical model of a highly generalisable, ATP-dependent, decision-making regulatory network, and show that cell-to-cell ATP variability changes the sets of decisions a cell can make. Our model shows that increasing intracellular energy levels can increase the number of supported stable phenotypes, corresponding to increased decision-making capacity. Model cells with sub-threshold intracellular energy are limited to a singular phenotype, forcing the adoption of a specific cell fate. We suggest that energetic differences between cells may be an important consideration to help explain observed variability in cellular decision-making across biological systems.

Mathematical model predicts anti-adhesion-antibiotic-debridement combination therapies can clear an antibiotic resistant infection.

As antimicrobial resistance increases, it is crucial to develop new treatment strategies to counter the emerging threat. In this paper, we consider combination therapies involving conventional antibiotics and debridement, coupled with a novel anti-adhesion therapy, and their use in the treatment of antimicrobial resistant burn wound infections. Our models predict that anti-adhesion-antibiotic-debridement combination therapies can eliminate a bacterial infection in cases where each treatment in isolation would fail. Antibiotics are assumed to have a bactericidal mode of action, killing bacteria, while debridement involves physically cleaning a wound (e.g. with a cloth); removing free bacteria. Anti-adhesion therapy can take a number of forms. Here we consider adhesion inhibitors consisting of polystyrene microbeads chemically coupled to a protein known as multivalent adhesion molecule 7, an adhesin which mediates the initial stages of attachment of many bacterial species to host cells. Adhesion inhibitors competitively inhibit bacteria from binding to host cells, thus rendering them susceptible to removal through debridement. An ordinary differential equation model is developed and the antibiotic-related parameters are fitted against new in vitro data gathered for the present study. The model is used to predict treatment outcomes and to suggest optimal treatment strategies. Our model predicts that anti-adhesion and antibiotic therapies will combine synergistically, producing a combined effect which is often greater than the sum of their individual effects, and that anti-adhesion-antibiotic-debridement combination therapy will be more effective than any of the treatment strategies used in isolation. Further, the use of inhibitors significantly reduces the minimum dose of antibiotics required to eliminate an infection, reducing the chances that bacteria will develop increased resistance. Lastly, we use our model to suggest treatment regimens capable of eliminating bacterial infections within clinically relevant timescales.

Predictive modelling of a novel anti-adhesion therapy to combat bacterial colonisation of burn wounds.

As the development of new classes of antibiotics slows, bacterial resistance to existing antibiotics is becoming an increasing problem. A potential solution is to develop treatment strategies with an alternative mode of action. We consider one such strategy: anti-adhesion therapy. Whereas antibiotics act directly upon bacteria, either killing them or inhibiting their growth, anti-adhesion therapy impedes the binding of bacteria to host cells. This prevents bacteria from deploying their arsenal of virulence mechanisms, while simultaneously rendering them more susceptible to natural and artificial clearance. In this paper, we consider a particular form of anti-adhesion therapy, involving biomimetic multivalent adhesion molecule 7 coupled polystyrene microbeads, which competitively inhibit the binding of bacteria to host cells. We develop a mathematical model, formulated as a system of ordinary differential equations, to describe inhibitor treatment of a Pseudomonas aeruginosa burn wound infection in the rat. Benchmarking our model against in vivo data from an ongoing experimental programme, we use the model to explain bacteria population dynamics and to predict the efficacy of a range of treatment strategies, with the aim of improving treatment outcome. The model consists of two physical compartments: the host cells and the exudate. It is found that, when effective in reducing the bacterial burden, inhibitor treatment operates both by preventing bacteria from binding to the host cells and by reducing the flux of daughter cells from the host cells into the exudate. Our model predicts that inhibitor treatment cannot eliminate the bacterial burden when used in isolation; however, when combined with regular or continuous debridement of the exudate, elimination is theoretically possible. Lastly, we present ways to improve therapeutic efficacy, as predicted by our mathematical model.

Robust Phagocyte Recruitment Controls the Opportunistic Fungal Pathogen Mucor circinelloides in Innate Granulomas In Vivo.

Mucormycosis is an emerging fungal infection with extremely high mortality rates in patients with defects in their innate immune response, specifically in functions mediated through phagocytes. However, we currently have a limited understanding of the molecular and cellular interactions between these innate immune effectors and mucormycete spores during the early immune response. Here, the early events of innate immune recruitment in response to infection by Mucor circinelloides spores are modeled by a combined in silico modeling approach and real-time in vivo microscopy. Phagocytes are rapidly recruited to the site of infection in a zebrafish larval model of mucormycosis. This robust early recruitment protects from disease onset in vivoIn silico analysis identified that protection is dependent on the number of phagocytes at the infection site, but not the speed of recruitment. The mathematical model highlights the role of proinflammatory signals for phagocyte recruitment and the importance of inhibition of spore germination for protection from active fungal disease. These in silico data are supported by an in vivo lack of fungal spore killing and lack of reactive oxygen burst, which together result in latent fungal infection. During this latent stage of infection, spores are controlled in innate granulomas in vivo Disease can be reactivated by immunosuppression. Together, these data represent the first in vivo real-time analysis of innate granuloma formation during the early stages of a fungal infection. The results highlight a potential latent stage during mucormycosis that should urgently be considered for clinical management of patients.IMPORTANCE Mucormycosis is a dramatic fungal infection frequently leading to the death of patients. We know little about the immune response to the fungus causing this infection, although evidence points toward defects in early immune events after infection. Here, we dissect this early immune response to infectious fungal spores. We show that specialized white blood cells (phagocytes) rapidly respond to these spores and accumulate around the fungus. However, we demonstrate that the mechanisms that enable phagocytes to kill the fungus fail, allowing for survival of spores. Instead a cluster of phagocytes resembling an early granuloma is formed around spores to control the latent infection. This study is the first detailed analysis of early granuloma formation during a fungal infection highlighting a latent stage that needs to be considered for clinical management of patients.

The Essential Genome of Escherichia coli K-12.

Transposon-directed insertion site sequencing (TraDIS) is a high-throughput method coupling transposon mutagenesis with short-fragment DNA sequencing. It is commonly used to identify essential genes. Single gene deletion libraries are considered the gold standard for identifying essential genes. Currently, the TraDIS method has not been benchmarked against such libraries, and therefore, it remains unclear whether the two methodologies are comparable. To address this, a high-density transposon library was constructed in Escherichia coli K-12. Essential genes predicted from sequencing of this library were compared to existing essential gene databases. To decrease false-positive identification of essential genes, statistical data analysis included corrections for both gene length and genome length. Through this analysis, new essential genes and genes previously incorrectly designated essential were identified. We show that manual analysis of TraDIS data reveals novel features that would not have been detected by statistical analysis alone. Examples include short essential regions within genes, orientation-dependent effects, and fine-resolution identification of genome and protein features. Recognition of these insertion profiles in transposon mutagenesis data sets will assist genome annotation of less well characterized genomes and provides new insights into bacterial physiology and biochemistry.IMPORTANCE Incentives to define lists of genes that are essential for bacterial survival include the identification of potential targets for antibacterial drug development, genes required for rapid growth for exploitation in biotechnology, and discovery of new biochemical pathways. To identify essential genes in Escherichia coli, we constructed a transposon mutant library of unprecedented density. Initial automated analysis of the resulting data revealed many discrepancies compared to the literature. We now report more extensive statistical analysis supported by both literature searches and detailed inspection of high-density TraDIS sequencing data for each putative essential gene for the E. coli model laboratory organism. This paper is important because it provides a better understanding of the essential genes of E. coli, reveals the limitations of relying on automated analysis alone, and provides a new standard for the analysis of TraDIS data.

Mathematical modelling of the antibiotic-induced morphological transition of Pseudomonas aeruginosa.

Here we formulate a mechanistic mathematical model to describe the growth dynamics of P. aeruginosa in the presence of the ß-lactam antibiotic meropenem. The model is mechanistic in the sense that carrying capacity is taken into account through the dynamics of nutrient availability rather than via logistic growth. In accordance with our experimental results we incorporate a sub-population of cells, differing in morphology from the normal bacillary shape of P. aeruginosa bacteria, which we assume have immunity from direct antibiotic action. By fitting this model to experimental data we obtain parameter values that give insight into the growth of a bacterial population that includes different cell morphologies. The analysis of two parameters sets, that produce different long term behaviour, allows us to manipulate the system theoretically in order to explore the advantages of a shape transition that may potentially be a mechanism that allows P. aeruginosa to withstand antibiotic effects. Our results suggest that inhibition of this shape transition may be detrimental to bacterial growth and thus suggest that the transition may be a defensive mechanism implemented by bacterial machinery. In addition to this we provide strong theoretical evidence for the potential therapeutic strategy of using antimicrobial peptides (AMPs) in combination with meropenem. This proposed combination therapy exploits the shape transition as AMPs induce cell lysis by forming pores in the cytoplasmic membrane, which becomes exposed in the spherical cells.

Synergistic Impacts of Organic Acids and pH on Growth of Pseudomonas aeruginosa: A Comparison of Parametric and Bayesian Non-parametric Methods to Model Growth.

Different weak organic acids have significant potential as topical treatments for wounds infected by opportunistic pathogens that are recalcitrant to standard treatments. These acids have long been used as bacteriostatic compounds in the food industry, and in some cases are already being used in the clinic. The effects of different organic acids vary with pH, concentration, and the specific organic acid used, but no studies to date on any opportunistic pathogens have examined the detailed interactions between these key variables in a controlled and systematic way. We have therefore comprehensively evaluated the effects of several different weak organic acids on growth of the opportunistic pathogen Pseudomonas aeruginosa. We used a semi-automated plate reader to generate growth profiles for two different strains (model laboratory strain PAO1 and clinical isolate PA1054 from a hospital burns unit) in a range of organic acids at different concentrations and pH, with a high level of replication for a total of 162,960 data points. We then compared two different modeling approaches for the interpretation of this time-resolved dataset: parametric logistic regression (with or without a component to include lag phase) vs. non-parametric Gaussian process (GP) regression. Because GP makes no prior assumptions about the nature of the growth, this method proved to be superior in cases where growth did not follow a standard sigmoid functional form, as is common when bacteria grow under stress. Acetic, propionic and butyric acids were all more detrimental to growth than the other acids tested, and although PA1054 grew better than PAO1 under non-stress conditions, this difference largely disappeared as the levels of stress increased. As expected from knowledge of how organic acids behave, their effect was significantly enhanced in combination with low pH, with this interaction being greatest in the case of propionic acid. Our approach lends itself to the characterization of combinatorial interactions between stressors, especially in cases where their impacts on growth render logistic growth models unsuitable.

Lipopolysaccharide structure impacts the entry kinetics of bacterial outer membrane vesicles into host cells.

Outer membrane vesicles are nano-sized microvesicles shed from the outer membrane of Gram-negative bacteria and play important roles in immune priming and disease pathogenesis. However, our current mechanistic understanding of vesicle-host cell interactions is limited by a lack of methods to study the rapid kinetics of vesicle entry and cargo delivery to host cells. Here, we describe a highly sensitive method to study the kinetics of vesicle entry into host cells in real-time using a genetically encoded, vesicle-targeted probe. We found that the route of vesicular uptake, and thus entry kinetics and efficiency, are shaped by bacterial cell wall composition. The presence of lipopolysaccharide O antigen enables vesicles to bypass clathrin-mediated endocytosis, which enhances both their entry rate and efficiency into host cells. Collectively, our findings highlight the composition of the bacterial cell wall as a major determinant of secretion-independent delivery of virulence factors during Gram-negative infections.

Synthesis of Depo-Medrol-chitosan hydrogel as new drug slow-release appliance and investigation of release kinetics by high-performance liquid chromatography.

The present study deals with preparation and optimization of a novel chitosan hydrogel-based matrix by suspension cross-linking method for controlled release of Depo-Medrol. The controlled release of Depo-Medrol for effective Rheumatoid arthritis disease has become an imperative field in the drug delivery system. In this context, it was intended to optimize loading circumstances by experimental design and also study the release kinetics of Depo-Medrol entrapped in the chitosan matrix in order to obtain maximal efficiency for drug loading. The optimum concentrations of chitosan (2.5 g), glutaraldehyde (3.05 µL) and Depo-Medrol (0.1 mg) were set up to achieve the highest value of drug loaded and the most sustained release from the chitosan matrix. In vitro monitoring of drug release kinetic using high-performance liquid chromatography showed that 73% of the Depo-Medrol was released within 120 min, whereas remained drug was released during the next 67 h. High correlation between first-order and Higuchi's kinetic models indicates a controlled diffusion of Depo-Medrol through the surrounding media. Moreover, recovery capacity >82% and entrapment efficiency of 58-88% were achieved under optimal conditions. Therefore, the new synthesized Depo Medrol-chitosan is an applicable appliance for arthritis therapy by slow release mechanism. Copyright © 2016 John Wiley & Sons, Ltd.