Framework as a Service, FaaS: Personalized Prebiotic Development for Infants with the Elements of Time and Parametric Modelling of In Vitro Fermentation

Abstract

We proposed a framework with parametric modeling to obtain biological relevant parameters from the total probiotic growth pattern and metabolite production curves. The lag phase, maximum increase rate, and maximum capacity were obtained via a 205-h exploratory In vitro fermentation of a library of 13 structural-characterized prebiotic candidates against an exclusively breastfed infant fecal inoculum. We also conducted 16S rRNA amplicon sequencing of the infant fecal inoculum. Moreover, we introduce a robust composite metabolite-based indicator that reflects the eubiosis/dysbiosis of microbiota to complement the conventional microbial markers. In terms of short-chain fatty acid, we discovered that polymeric beta-glucans from barley demonstrated potential as prebiotic candidates, while alpha-glucans as glycogen showed the least dissolved ammonia production. In terms of total probiotic, beta-glucans from oat and mushroom sclerotia of Pleurotus tuber-regium showed comparable sustainability when compared to alpha-glucans after 48 h. Being classical prebiotic, galacto-oligosaccharides gave the second-highest metabolite-based indicator, followed by lactose. While limited improvement could be made to lactose and oligosaccharides, polymeric beta-glucans from barley avails more capacity for novel prebiotic development, such as structural modification. We anticipate that more similar parallel screening with the element of time and parametric modeling will provide more novel insights.