TY - JOUR
T1 - Perspective: Leveraging the Gut Microbiota to Predict Personalized Responses to Dietary, Prebiotic, and Probiotic Interventions
AU - Gibbons, Sean M.
AU - Gurry, Thomas
AU - Lampe, Johanna W.
AU - Chakrabarti, Anirikh
AU - Dam, Veerle
AU - Everard, Amandine
AU - Goas, Almudena
AU - Gross, Gabriele
AU - Kleerebezem, Michiel
AU - Lane, Jonathan
AU - Maukonen, Johanna
AU - Penna, Ana Lucia Barretto
AU - Pot, Bruno
AU - Valdes, Ana M.
AU - Walton, Gemma
AU - Weiss, Adrienne
AU - Zanzer, Yoghatama Cindya
AU - Venlet, Naomi V.
AU - Miani, Michela
PY - 2022/9
Y1 - 2022/9
N2 - Humans often show variable responses to dietary, prebiotic, and probiotic interventions. Emerging evidence indicates that the gut microbiota is a key determinant for this population heterogeneity. Here, we provide an overview of some of the major computational and experimental tools being applied to critical questions of microbiota-mediated personalized nutrition and health. First, we discuss the latest advances in in silico modeling of the microbiota-nutrition-health axis, including the application of statistical, mechanistic, and hybrid artificial intelligence models. Second, we address high-throughput in vitro techniques for assessing interindividual heterogeneity, from ex vivo batch culturing of stool and continuous culturing in anaerobic bioreactors, to more sophisticated organ-on-a-chip models that integrate both host and microbial compartments. Third, we explore in vivo approaches for better understanding of personalized, microbiota-mediated responses to diet, prebiotics, and probiotics, from nonhuman animal models and human observational studies, to human feeding trials and crossover interventions. We highlight examples of existing, consumer-facing precision nutrition platforms that are currently leveraging the gut microbiota. Furthermore, we discuss how the integration of a broader set of the tools and techniques described in this piece can generate the data necessary to support a greater diversity of precision nutrition strategies. Finally, we present a vision of a precision nutrition and healthcare future, which leverages the gut microbiota to design effective, individual-specific interventions.
AB - Humans often show variable responses to dietary, prebiotic, and probiotic interventions. Emerging evidence indicates that the gut microbiota is a key determinant for this population heterogeneity. Here, we provide an overview of some of the major computational and experimental tools being applied to critical questions of microbiota-mediated personalized nutrition and health. First, we discuss the latest advances in in silico modeling of the microbiota-nutrition-health axis, including the application of statistical, mechanistic, and hybrid artificial intelligence models. Second, we address high-throughput in vitro techniques for assessing interindividual heterogeneity, from ex vivo batch culturing of stool and continuous culturing in anaerobic bioreactors, to more sophisticated organ-on-a-chip models that integrate both host and microbial compartments. Third, we explore in vivo approaches for better understanding of personalized, microbiota-mediated responses to diet, prebiotics, and probiotics, from nonhuman animal models and human observational studies, to human feeding trials and crossover interventions. We highlight examples of existing, consumer-facing precision nutrition platforms that are currently leveraging the gut microbiota. Furthermore, we discuss how the integration of a broader set of the tools and techniques described in this piece can generate the data necessary to support a greater diversity of precision nutrition strategies. Finally, we present a vision of a precision nutrition and healthcare future, which leverages the gut microbiota to design effective, individual-specific interventions.
KW - diet
KW - microbiome
KW - microbiota
KW - personalized healthcare
KW - personalized nutrition
KW - prebiotic
KW - precision healthcare
KW - precision nutrition
KW - probiotic
U2 - 10.1093/advances/nmac075
DO - 10.1093/advances/nmac075
M3 - Article
C2 - 35776947
AN - SCOPUS:85139535635
SN - 2161-8313
VL - 13
SP - 1450
EP - 1461
JO - Advances in nutrition (Bethesda, Md.)
JF - Advances in nutrition (Bethesda, Md.)
IS - 5
ER -