Investigation of diabetes mellitus induced changes to the respiratory microbiome and its use as a predictor of susceptibility to infection.

Airway surface liquid (ASL) coats the lumen of the airway with a thin layer of fluid and plays an important role in the defence against infection. The concentration of glucose in the ASL is dependent on glucose in the blood; people with hyperglycaemia (such as diabetic patients) will have more glucose in ASL. It has been demonstrated that an increase in ASL glucose concentration is linked with an increased risk of respiratory colonisation and luminal growth of pathogenic bacteria putting hyperglycaemic patients at a higher risk of pulmonary infections.
A microbiome is defined as a combination of all microbes, and all of genes of microbes, present in a human body. A microbiome can be modified in various ways; altering of total load of bacteria, change in the dominant specie or loss of sentinel species. Distortion of a microbiome could be a potential contributor to the decline of lung function; further increasing the risk of infection.
With the introduction of High-throughput sequence (hTs), it has become possible to study pulmonary microbiome in detail independent of culturing techniques. hTs techniques are based on the bacterial 16S ribosomal RNA (rRNA) allowing analysis of the whole microbiome at once. 16S rRNA is ubiquitous in bacteria and sequencing information allows species identification at high sensitivity. This may aid our understanding of the role of the microbiome in physiological processes, metabolism and disease progression in the host.
Regulation of blood glucose in diabetic patients will be investigated to determine if lung microbiota reverts to a healthy composition and whether this results in a decreased chance of chronic lung infection. Monitoring changes to the microbiota may highlight dysregulation in high risk patients. This may allow intervention before infection takes hold cutting the cost of further treatment. Furthermore, if patterns of lung microbiota are shown to be similar in both sputum samples and saliva/nasal swabs it would allow for less invasive diagnosis in future.
First, It will be assessed whether lung microbiota diversity and relative abundance of potentially pathogenic organisms is altered in mice with diabetes compared to controls. Bronchoalveolar lavage (BAL) fluids will be collected from both groups. DNA from mouse BAL samples will be extracted and used in 16S rRNA polymerase chain reaction (PCR) amplification and MiSeq analysis. Data will be analysed using Quantitative Insights into Microbial Ecology (QIIME) - open-source bioinformatics pipeline for performing microbiome analysis and GreenGenes 16S rRNA gene database.
The second part of the research will focus on clinical samples. The objective will be to determine whether microbial diversity, and relative abundance of potentially pathogenic organisms, in lung microbiota are altered in sputum and oral wash samples from patients with diabetes compared to non-diabetic patients. Use of oral washes as an alternative non-invasive approach to study lung microbiome will be investigated.
Lung microbiome of diabetic vs non-diabetic patients with chronic lung diseases such as COPD and CF would be compared to determine the effect of diabetes on lung microbiome.