Non-invasive monitoring of changes in exhaled markers of airway inflammation in Thoroughbred racehorses

Exhaled breath (EB) and exhaled breath condensate (EBC) contain numerous volatile gases and a wide-array of non-volatile compounds, several of which have been investigated as markers of lower airway inflammation in human and veterinary medicine and have been used to diagnose and monitor diseases associated with pulmonary inflammation. The identification of reliable biomarkers within EB and EBC is an active research focus with the common goal of establishing non-invasive and repeatable assessment of respiratory health and disease in mammals. The application of EB and EBC analysis holds considerable appeal in the investigation of respiratory disease in Thoroughbred racehorses, as inflammatory airway disease (IAD) is a common cause for poor performance in this population of animals. This study documented that EB and EBC samples can be safely collected from Thoroughbred racehorses in their own environment, without adverse effect or interference with the horse’s training regimen. The use of off-line collection and analysis of exhaled gases via chemiluminescence is suitable for the measurement of exhaled carbon monoxide, but is not appropriate for analyzing exhaled nitric oxide in horses. Significant changes in the concentration of exhaled CO and the pH of EBC occurred in response to strenuous exercise and when exercising in different environmental temperatures. Exhaled CO was associated with tracheal mucus score (and the number of neutrophils in the mucus) and EBC pH was significantly different in horses with evidence of neutrophilic IAD compared to horses without IAD. Numerous physiological and environmental variables were identified as confounding factors in the assessment of both exhaled CO and EBC pH, with respiratory rate prior to EB collection, and during EBC collection, consistently identified as an explanatory variable influencing the concentration of exhaled biomarkers. Further studies in EB and EBC analysis in horses need to focus on objectively accounting for key respiratory dynamics during sample collection.

The impact of denture related disease on the oral microbiome of denture wearers

Advances in healthcare over the last 100 years has resulted in an ever increasing elderly population. This presents greater challenges for adequate systemic and oral healthcare delivery. With increasing age there is a natural decline in oral health, leading to the loss of teeth and ultimately for some having to wear denture prosthesis. It is currently estimated that approximately one fifth of the UK and US populations have some form of removable prosthesis. The microbiology of denture induced mucosal inflammation is a pivotal factor to consider in denture care management, similar to many other oral diseases of microbial influence, such as caries, gingivitis and periodontitis. Dentures support the growth of microbial biofilms, structures commonly known as denture plaque. Microbiologically, denture stomatitis (DS) is a disease primarily considered to be of yeast aetiology, with the literature disproportionately focussed on Candida spp. However, the denture surface is capable of carrying up to 1011 microbes per milligram, the majority of which are bacteria. Thus it is apparent that denture plaque is more diverse than we assume. There is a fundamental gap in our understanding of the bacterial composition of denture plaque and the role that they may play in denture related disease such as DS. This is categorised as inflammation of the oral mucosa, a disease affecting around half of all denture wearers. It has been proposed that bacteria and fungi interact on the denture surface and that these polymicrobial interactions lead to synergism and increased DS pathogenesis. Therefore, understanding the denture microbiome composition is the key step to beginning to understand disease pathogenesis, and ultimately help improve treatments and identify novel targets for therapeutic and preventative strategies. A group of 131 patients were included within this study in which they provided samples from their dentures, palatal mucosa, saliva and dental plaque. Microbes residing on the denture surface were quantified using standard Miles and Misra culture technique which investigated the presence of Candida, aerobes and anaerobes. These clinical samples also underwent next generation sequencing using the Miseq Illumina platform to give a more global representation of the microbes present at each of these sites in the oral cavity of these denture wearers. This data was then used to compare the composition and diversity of denture, mucosal and dental plaque between one another, as well as between healthy and diseased individuals. Additional comparisons included denture type and the presence or absence of natural teeth. Furthermore, microbiome data was used to assess differences between patients with varying levels of oral hygiene. The host response to the denture microbiome was investigated by screening the patients saliva for the presence and quantification of a range of antimicrobial peptides that are associated with the oral cavity. Based on the microbiome data an in vitro biofilm model was developed that reflected the composition of denture plaque. These biofilms were then used to assess quantitative and compositional changes over time and in response to denture cleansing treatments. Finally, the systemic implications of denture plaque were assessed by screening denture plaque samples for the presence of nine well known respiratory pathogens using quantitative PCR. The results from this study have shown that the bacterial microbiome composition of denture wearers is not consistent throughout the mouth and varies depending on sample site. Moreover, the presence of natural dentition has a significant impact on the microbiome composition. As for healthy and diseased patients the data suggests that compositional changes responsible for disease progression are occurring at the mucosa, and that dentures may in fact be a reservoir for these microbes. In terms of denture hygiene practices, sleeping with a denture in situ was found to be a common occurrence. Furthermore, significant shifts in denture microbiome composition were found in these individuals when compared to the denture microbiome of those that removed their denture at night. As for the host response, some antimicrobial peptides were found to be significantly reduced in the absence of natural dentition, indicating that the oral immune response is gradually impaired with the loss of teeth. This study also identified potentially serious systemic implications in terms of respiratory infection, as 64.6% of patients carried respiratory pathogens on their denture. In conclusion, this is the first study to provide a detailed understanding of the oral microbiome of denture wearers, and has provided evidence that DS development is more complex than simply a candidal infection. Both fungal and bacterial kingdoms clearly play a role in defining the progression of DS. The biofilm model created in this study demonstrated its potential as a platform to test novel actives. Future use of this model will aid in greater understanding of host: biofilm interactions. Such findings are applicable to oral health and beyond, and may help to identify novel therapeutic targets for the treatment of DS and other biofilm associated diseases.

Exploring the role of miR-34a in regulating adipose inflammation during obesity

Background: Obesity is not a new disease, with roots that can be traced back to 400 BC. However, with the staggering increase in individuals that are overweight and obese since the 1980s, now over a quarter of individuals in Europe and the Americas are classed as obese. This presents a global health problem that needs to be addressed with novel therapies. It is now well accepted that obesity is a chronic, low-grade inflammatory condition that could predispose individuals to a number of comorbidities. Obesity is associated with cardiovascular diseases (CVDs) and type 2 diabetes (T2D) as part of “the metabolic syndrome,” and as first identified by Dr Vauge, central distribution of white adipose tissue (WAT) is an important risk factor in the development of these diseases. Subsequently, visceral WAT (vWAT) was shown to be an important factor in this association with CVDs and T2D, and increasing inflammation. As the obese WAT expands, mainly through hypertrophy, there is an increase in inflammation that recruits numerous immune cells to the tissue that further exacerbate this inflammation, causing local and systemic inflammatory and metabolic effects. One of the main types of immune cell involved in this pathogenic process is pro-inflammatory M1 adipose tissue macrophages (ATMs). MicroRNAs (miRNAs) are a species of small RNAs that post-transcriptionally regulate gene expression by targeting gene mRNA, causing its degradation or translational repression. These miRNAs are promiscuous, regulating numerous genes and pathways involved in a disease, making them useful therapeutic targets, but also difficult to study. miR-34a has been shown to increase in the serum, liver, pancreas, and subcutaneous (sc)WAT of patients with obesity, non- alcoholic fatty liver disease (NAFLD) and T2D. Additionally, miR-34a has been shown to regulate a number of metabolic and inflammatory genes in numerous cell types, including those in macrophages. However, the role of miR-34a in regulating vWAT metabolism and inflammation is poorly understood. Hypothesis: miR-34a is dysregulated in the adipose tissue during obesity, causing dysregulation of metabolic and inflammatory pathways in adipocytes and ATMs that contribute to adipose inflammation and obesity’s comorbidities, particularly T2D. Method/Results: The role of miR-34a in adipose inflammation was investigated using a murine miR-34a-/- diet-induced obesity model, and primary in vitro models of adipocyte differentiation and inflammatory bone marrow-derived macrophages (BMDMs). miR-34a was shown to be ubiquitously expressed throughout the murine epididymal (e)WAT of obese high-fat diet (HFD)-fed WT mice and ob/ob mice, as well as omental WAT from patients with obesity. Additionally, miR-34a transcripts were increased in the liver and brown adipose tissue (BAT) of ob/ob and HFD-fed WT mice, compared to WT controls. When miR-34a-/- mice were fed HFD ad libitum for 24 weeks they were significantly heavier than their WT counterparts by the end of the study. Ex vivo examinations showed that miR-34a-/- eWAT had a smaller adipocyte area on chow, which significantly increased to WT levels during HFD-feeding. Additionally, miR-34a-/- eWAT showed basal increases in cholesterol and fatty acid metabolism genes Cd36, Hmgcr, Lxrα, Pgc1α, and Fasn. miR-34a-/- iBAT showed basal reductions in Cebpα and Cebpβ, with increased Pgc1α expression during HFD- feeding. The miR-34a-/- liver additionally showed increased basal transcript expression of Pgc1α, suggesting miR-34a may broadly regulate PGC1α. Accompanying the ex vivo changes in cholesterol and fatty acid metabolism genes, in vitro miR-34a-/- white adipocytes showed increased lipid content. An F4/80high macrophage population was identified in HFD-fed miR-34a-/- eWAT, with increased Il-10 transcripts and serum IL-5 protein. Following these ex vivo observations, BMDMs from WT mice upregulated miR-34a expression in response to TNFα stimulation. Additionally, miR-34a-/- BMDMs showed an ablated CXCL1 response to TNFα. Conclusion: These findings suggest miR-34a has a multi-factorial role in controlling a susceptibility to obesity, by regulating inflammatory and metabolic pathways, potentially through regulation of PGC1α.