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Short-chain fatty acids (SCFAs), including acetate, propionate and butyrate,are organic fatty-acids that are produced when indigested carbohydrates arefermented in the colon by gut-bacteria. Butyrate is especially considered abeneficial compound in relation to gut health and the maintenance of colonichomeostasis. Little is known about butyrate production and the currentmeasurement methods of fecal samples are not representative and there is astrong unmet need to measure SCFAs in-vivo to further understand their role andeffect on colonic function in human gut health and disease. The general aim ofthe project is to develop a novel sensor based on infrared technology that iscapable of online detecting short chain fatty acids (SCFA; e.g. acetate,propionate and butyrate) and other small biomolecules (e.g. ammonium) producedin bioreactors. Whereas currently such levels of small biomolecules are usuallynot detected online due to practical constraints (sampling-analysis-processingof data), reliable online detection could significantly decrease analysiscosts. Further, it would allow to perform online quality control of thebioreactors and allow to e.g. detect deviating values at an early stage. Hence,one can react much faster tackling certain problems which will further improvethe quality of each experiment. Using machine learning algorithms to processthe sensor signals, the results from testing in a so-called artificial gutsetup are described in this technical report.

Using infrared gas sensors in an in-vitro dynamic gut model for detecting short-chain fatty-acids: Technical Report