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A mixed culture (polymicrobial) biofilm provides a favorable environment for pathogens to persist in the food processing environment and to contaminate food products. Inactivation and eradication of such biofilms from food processing environments are achieved by using harsh disinfectants, but their toxicity and environmentally hostile characteristics are unsustainable. This study aims to use food-grade natural nanoparticulated antimicrobials to control mixed-culture biofilms. Chitosan, a natural broad-spectrum antimicrobial biopolymer (polysaccharide) from crustaceans, was derivatized to produce chitosan nanoparticles (ChNP) as a carrier for another broad-spectrum antimicrobial agent, ε-poly-L-lysine (PL), to synthesize ChNP-PL conjugate. The antimicrobial activity of ChNP and ChNP-PL was tested against mixed-culture biofilms. ChNP-PL (~100 nm) exhibited a synergistic antimicrobial and anti-biofilm effect against mono or mixed-culture biofilms of five foodborne pathogens, including Listeria monocytogenes, Staphylococcus aureus, Salmonella enterica serovar Enteritidis, Escherichia coli O157:H7, and Pseudomonas aeruginosa. ChNP-PL treatment prevented biofilm formation by mono or mixed cultures of L. monocytogenes, P. aeruginosa, and E. coli O157:H7, and bacterial counts were either below the detection limit or caused 3.5–5 log reduction. ChNP-PL also inactivated preformed biofilms. In monoculture biofilm, ChNP-PL treatment reduced L. monocytogenes counts by 4.5 logs, S. Enteritidis by 2 logs, E. coli by 2 logs, and S. aureus by 0.5 logs, while ChNP-PL had no inhibitory effect on P. aeruginosa. In vitro mammalian cell-based cytotoxicity analysis confirmed ChNP-PL to have no deleterious effect on intestinal HCT-8 cell line. In conclusion, our results show ChNP-PL has strong potential to prevent the formation or inactivation of preformed polymicrobial biofilms of foodborne pathogens.

Objectives The upper respiratory tract is the major entry site for Streptococcus pyogenes and influenza virus. Vaccine strategies that activate mucosal immunity could significantly reduce morbidity and mortality because of these pathogens. The severity of influenza is significantly greater if a streptococcal infection occurs during the viraemic period and generally viral infections complicated by a subsequent bacterial infection are known as super‐infections. We describe an innovative vaccine strategy against influenza virus:S. pyogenes super‐infection. Moreover, we provide the first description of a liposomal multi‐pathogen‐based platform that enables the incorporation of both viral and bacterial antigens into a vaccine and constitutes a transformative development. Methods Specifically, we have explored a vaccination strategy with biocompatible liposomes that express conserved streptococcal and influenza A virus B‐cell epitopes on their surface and contain encapsulated diphtheria toxoid as a source of T‐cell help. The vaccine is adjuvanted by inclusion of the synthetic analogue of monophosphoryl lipid A, 3D‐PHAD. Results We observe that this vaccine construct induces an Immunoglobulin A (IgA) response in both mice and ferrets. Vaccination reduces viral load in ferrets from influenza challenge and protects mice from both pathogens. Notably, vaccination significantly reduces both mortality and morbidity associated with a super‐infection. Conclusion The vaccine design is modular and could be adapted to include B‐cell epitopes from other mucosal pathogens where an IgA response is required for protection., In this study, we report on the potential of a modular multi‐pathogen mucosal vaccine. We found that this vaccine construct induces an Immunoglobulin A (IgA) response in both mice and ferrets. Vaccination reduces viral load in ferrets from influenza challenge and protects mice from influenza virus:S. pyogenes super‐infection.

We report new molecular evidence of locally acquired dengue virus infections in Ghana. We detected dengue viral RNA among children with suspected malaria by using a multipathogen real-time PCR. Subsequent sequence analysis revealed a close relationship with dengue virus serotype 2, which was implicated in a 2016 outbreak in Burkina Faso.

Background Increased computational resources have made individual based models popular for modelling epidemics. They have the advantage of incorporating heterogeneous features, including realistic population structures (like e.g. households). Existing stochastic simulation studies of epidemics, however, have been developed mainly for incorporating single pathogen scenarios although the effect of different pathogens might directly or indirectly (e.g. via contact reductions) effect the spread of each pathogen. The goal of this work was to simulate a stochastic agent based system incorporating the effect of multiple pathogens, accounting for the household based transmission process and the dependency among pathogens. Methods With the help of simulations from such a system, we observed the behaviour of the epidemics in different scenarios. The scenarios included different household size distributions, dependency versus independency of pathogens, and also the degree of dependency expressed through household isolation during symptomatic phase of individuals. Generalized additive models were used to model the association between the epidemiological parameters of interest on the variation in the parameter values from the simulation data. All the simulations and statistical analyses were performed using R 3.4.0. Results We demonstrated the importance of considering pathogen dependency using two pathogens, and showing the difference when considered independent versus dependent. Additionally for the general scenario with more pathogens, the assumption of dependency among pathogens and the household size distribution in the population cohort was found to be effective in containing the epidemic process. Additionally, populations with larger household sizes reached the epidemic peak faster than societies with smaller household sizes but dependencies among pathogens did not affect this outcome significantly. Larger households had more infections in all population cohort examples considered in our simulations. Increase in household isolation coefficient for pathogen dependency also could control the epidemic process. Conclusion Presence of multiple pathogens and their interaction can impact the behaviour of an epidemic across cohorts with different household size distributions. Future household cohort studies identifying multiple pathogens will provide useful data to verify the interaction processes in such an infectious disease system. Electronic supplementary material The online version of this article (10.1186/s12976-017-0072-7) contains supplementary material, which is available to authorized users.