Comparison of the antibacterial activity of essential oils and extracts of medicinal and culinary herbs to investigate potential new treatments for irritable bowel syndrome.

BACKGROUND: Irritable bowel syndrome (IBS) is a common functional gastrointestinal disorder, which may result from alteration of the gastrointestinal microbiota following gastrointestinal infection, or with intestinal dysbiosis or small intestinal bacterial overgrowth. This may be treated with antibiotics, but there is concern that widespread antibiotic use might lead to antibiotic resistance. Some herbal medicines have been shown to be beneficial, but their mechanism(s) of action remain incompletely understood. To try to understand whether antibacterial properties might be involved in the efficacy of these herbal medicines, and to investigate potential new treatments for IBS, we have conducted a preliminary study in vitro to compare the antibacterial activity of the essential oils of culinary and medicinal herbs against the bacterium, Esherichia coli. METHODS: Essential oils were tested for their ability to inhibit E. coli growth in disc diffusion assays and in liquid culture, and to kill E. coli in a zone of clearance assay. Extracts of coriander, lemon balm and spearmint leaves were tested for their antibacterial activity in the disc diffusion assay. Disc diffusion and zone of clearance assays were analysed by two-tailed t tests whereas ANOVA was performed for the turbidometric assays. RESULTS: Most of the oils exhibited antibacterial activity in all three assays, however peppermint, lemon balm and coriander seed oils were most potent, with peppermint and coriander seed oils being more potent than the antibiotic rifaximin in the disc diffusion assay. The compounds present in these oils were identified by gas chromatography mass spectrometry. Finally, extracts were made of spearmint, lemon balm and coriander leaves with various solvents and these were tested for their antibacterial activity against E. coli in the disc diffusion assay. In each case, extracts made with ethanol and methanol exhibited potent antibacterial activity. CONCLUSIONS: Many of the essential oils had antibacterial activity in the three assays, suggesting that they would be good candidates for testing in clinical trials. The observed antibacterial activity of ethanolic extracts of coriander, lemon balm and spearmint leaves suggests a mechanistic explanation for the efficacy of a mixture of coriander, lemon balm and mint extracts against IBS in a published clinical trial.

Patterning of antibodies using flexographic printing.

Antibodies were patterned onto flexible plastic films using the flexographic printing process. An ink formulation was developed using high molecular weight polyvinyl alcohol in carbonate-bicarbonate buffer. In order to aid both antibody adhesion and the quality of definition in the printed features, a nitrocellulose coating was developed that was capable of being discretely patterned, thus increasing the signal-to-noise ratio of an antibody array. Printing antibody features such as dots, squares, text, and fine lines were reproduced effectively. Furthermore, this process could be easily adapted for printing of other biological materials, including, but not limited to, enzymes, DNA, proteins, aptamers, and cells.

Machine learning methods on exhaled volatile organic compounds for distinguishing COPD patients from healthy controls.

Exhaled volatile organic compounds (VOCs) have shown promise in diagnosing chronic obstructive pulmonary disease (COPD) but studies have been limited by small sample size and potential confounders. An investigation was conducted in order to establish whether combinations of VOCs could identify COPD patients from age and BMI matched controls. Breath samples were collected from 119 stable COPD patients and 63 healthy controls. The samples were collected with a portable apparatus, and then assayed by gas chromatography and mass spectroscopy. Machine learning approaches were applied to the data and the automatically generated models were assessed using classification accuracy and receiver operating characteristic (ROC) curves. Cross-validation of the combinations correctly predicted the diagnosis in 79% of COPD patients and 64% of controls and an optimum area under the ROC curve of 0.82 was obtained. Comparison of current and ex smokers within the COPD group showed that smoking status was likely to affect the classification; with correct prediction of smoking status in 85% of COPD subjects. When current smokers were omitted from the analysis, prediction of COPD was similar at 78% but correct prediction of controls was increased to 74%. Applying different analytical methods to the largest group of subjects so far, suggests VOC analysis holds promise for diagnosing COPD but smoking status needs to be balanced.