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PP-006 The gut in health and disease: scenting the difference by “electronic nose”
  1. R P Arasaradnam1,
  2. N Quraishi2,
  3. S Kumar3,
  4. C Nwokolo2,
  5. K D Bardhan4,
  6. J Covington5
  1. 1CSRI, University of Warwick, Coventry, UK
  2. 2Department of Gastroenterology, Coventry, UK
  3. 3Clinical Sciences Research Institute (CSRI), University Hospitals Coventry and Warwickshire (UHCW), Coventry, UK
  4. 4Department of Gastroenterology, Rotherham Foundation NHS Trust, Rotherham, UK
  5. 5School of Engineering, University of Warwick, Coventry, UK

Abstract

Introduction Resident colonic bacteria (anaerobes and firmicutes) ferment undigested fibre. The balance between their large species number is influenced by the host genetic make up. An individuals “fermentation profile” (FP) is therefore likely to comprise a stable “personal signature” and a variable portion, which is influenced by the gut environment—diet and to a lesser extent drugs, thus offering an insight into colonic microbial health. A method of monitoring FP is by analysing the gaseous release that emanates off a patient's urine or faecal sample. This can then be characterised using various techniques, but two options are: Artificial olfaction (the so called electronic nose or e-nose), which offers a method to rapidly identify disease groups based on the a complete “bio-odorant signature”; Gas Chromatography/Mass Spectrometry, which seeks to identify all the chemical components within a sample.

Aim Pilot study using an “e-nose” to determine if disease groups can be distinguished and identified from faeces and urine samples.

Methods Subjects and patients: two healthy (normal) volunteers; Ulcerative Colitis (n=1; active disease induced into remission), Crohns Disease (n=1). Biological samples of faeces and urine were collected and urine samples were analysed. Samples were prepared in universal containers (10 ml) and heated to 38±0.1°C. The headspace (the air above the sample) was then analysed using a Cyrano A320 (Smith Detection) e-nose, employing 32 carbon black compositae chemoresistive chemical sensors. These instruments employ a series of sensors with overlapping sensitivity, thus creating a “fingerprint” of the total chemical composition of a sample (as with the human nose). Each headspace was sampled for 30 s, and purged for a further 30 s in laboratory air. The differential response between the sample and the background air was used for analysis.

Results The PCA plot generated (not shown; high resolution) demonstrates the e-nose's capability to distinguish between disease groups with >90% selectivity. Specifically there was polarity between UC and CD subjects and importantly, shifting of profile in the UC subject with treatment towards a normal configuration.

Conclusion 1. The e-nose offers a rapid and promising way of investigating FPs in health and disease. 2. Clear differences in gaseous profile between volunteers and disease subjects were demonstrated. 3. The gaseous profile changes with treatment. The study of FPs using e-nose is novel and offers a new insight into “scenting” gut health.

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