Blood or Serum Exposure Induce Global Transcriptional Changes, Altered Antigenic Profile, and Increased Cytotoxicity by Classical Bordetellae

The classical bordetellae sense and respond to a variety of environments outside and within their mammalian hosts. By causing inflammation and tissue damage, we reasoned that bordetellae are likely to encounter components of blood and/or serum during the course of a respiratory infection, and that detecting and responding to these would be advantageous. Therefore, we hypothesized that classical bordetellae have the ability to sense and respond to blood or serum. Blood or serum exposure resulted in substantial transcriptional changes in Bordetella bronchiseptica, including enhanced expression of many virulence-associated genes. Exposure to blood or serum additionally elicited production of multiple antigens not otherwise detectable, and led to increased bacterial cytotoxicity against macrophages. Transcriptional responses to blood/serum were observed in a Bvg− phase-locked mutant, indicating that the response is not solely dependent on a functional BvgAS system. Similar transcriptional responses to blood/serum were observed for the other classical bordetellae, Bordetella pertussis and Bordetella parapertussis. These data suggest the classical bordetellae respond to signals present in blood and serum by changing their behavior in ways that likely contribute to their remarkable success, via effects on pathogenesis, persistence and/or transmission between hosts

Computational health engineering applied to model infectious diseases and antimicrobial resistance spread

Infectious diseases are the primary cause of mortality worldwide. The dangers of infectious disease are compounded with antimicrobial resistance, which remains the greatest concern for human health. Although novel approaches are under investigation, the World Health Organization predicts that by 2050, septicaemia caused by antimicrobial resistant bacteria could result in 10 million deaths per year. One of the main challenges in medical microbiology is to develop novel experimental approaches, which enable a better understanding of bacterial infections and antimicrobial resistance. After the introduction of whole genome sequencing, there was a great improvement in bacterial detection and identification, which also enabled the characterization of virulence factors and antimicrobial resistance genes. Today, the use of in silico experiments jointly with computational and machine learning offer an in depth understanding of systems biology, allowing us to use this knowledge for the prevention, prediction, and control of infectious disease. Herein, the aim of this review is to discuss the latest advances in human health engineering and their applicability in the control of infectious diseases. An in-depth knowledge of host-pathogen-protein interactions, combined with a better understanding of a host's immune response and bacterial fitness, are key determinants for halting infectious diseases and antimicrobial resistance dissemination

Use of Biopolymers in Mucosally-Administered Vaccinations for Respiratory Disease

Communicable respiratory infections are the cause of a significant number of infectious diseases. The introduction of vaccinations has greatly improved this situation. Moreover, adjuvants have allowed for vaccines to be more effective with fewer adverse side effects. However, there is still space for improvement because while the more common injected formulations induce a systematic immunity, they do not confer the mucosal immunity needed for more thorough prevention of the spread of respiratory disease. Intranasal formulations provide systemic and mucosal immune protection, but they have the potential for more serious side effects and a less robust immune response. This review looks at seven different adjuvants—chitosan, starch, alginate, gellan, β-glucan, emulsan and hyaluronic acid—and their prospective ability to improve intranasal vaccines as adjuvants and antigen delivery systems

Novel Therapeutic Strategies Applied to Pseudomonas aeruginosa Infections in Cystic Fibrosis

Cystic fibrosis (CF) is one of the most prevalent genetic diseases and a total of 1700 different genetic mutations can cause this condition. Patients that suffer this disease have a thickening of the mucus, creating an environment that promotes bacterial infections. Pseudomonas aeruginosa is a ubiquitous bacterium, which is frequently found in the lungs of CF patients. P. aeruginosa is known for its high level of antibiotic resistance as well as its high rate of mutation that allows it to rapidly evolve and adapt to a multitude of conditions. When a CF lung is infected with P. aeruginosa, the decay of the patient is accelerated, but there is little that can be done apart from controlling the infection with antibiotics. Novel strategies to control P. aeruginosa infection are imperative, and nanotechnology provides novel approaches to drug delivery that are more efficient than classic antibiotic treatments. These drug delivery systems are offering new prospects, especially for these patients with special mucus conditions and bacterial characteristics that limit antibiotic use