The complexities of the diet-microbiome relationship: advances and perspectives

Abstract

Personalised dietary modulation of the gut microbiota may be key to disease management. Current investigations provide a broad understanding of the impact of diet on the composition and activity of the gut microbiota, yet detailed knowledge in applying diet as an actionable tool remains limited. Further to the relative novelty of the field, approaches are yet to be standardised and extremely heterogeneous research outcomes have ensued. This may be related to confounders associated with complexities in capturing an accurate representation of both diet and the gut microbiota. This review discusses the intricacies and current methodologies of diet-microbial relations, the implications and limitations of these investigative approaches, and future considerations that may assist in accelerating applications. New investigations should consider improved collection of dietary data, further characterisation of mechanistic interactions, and an increased focus on -omic technologies such as metabolomics to describe the bacterial and metabolic activity of food degradation, together with its crosstalk with the host. Furthermore, clinical evidence with health outcomes is required before therapeutic dietary strategies for microbial amelioration can be made. The potential to reach detailed understanding of diet-microbiota relations may depend on re-evaluation, progression, and unification of research methodologies, which consider the complexities of these interactions.

Keywords: Diet; Gut microbiome; Personalised nutrition; Research methods.

Fig. 1

Understanding interactions between microbes, the microbiome, and the host both locally and systemically to enable its manipulation in order to improve human health. Suggested approaches for the characterisation of (1) intra-microbe interactions include in vitro mono- and co-culture systems; (2) inter-microbe interactions include in vitro co-culture and mass culture systems alongside quorum sensors to detect autoinducers that orchestrate collective behaviours [36, 37]; (3) communities include in vitro synthetic continuous communities with novel microarray technologies [38]; (4) spatial organisation include confocal microscopy integrated with multi-dimension algorithms alongside multi-omic technologies [39]; and (5) local host-microbe interactions include in vivo animal models accompanied by metabolomics providing a direct functional output of the metabolite profile, a result of local-host-microbial interactions [40], whereby the simultaneous profiling and integration of various -omic technologies is necessary to then identify (6) interactions at the molecular level systemically [40]. Image created with Biorender.com

Fig. 2

Current approaches vs. ideal approaches (image modified from Leeming et al. [15]). Current microbiome-diet-host approaches carry a number of caveats which may contribute to highly heterogeneous responses, such as the individualised microbiome [15]. A new ideal approach that may allow for further elucidation of diet-microbial-host relations includes stratification by microbial signature, collection of habitual diet data, longitudinal sampling and big data, machine learning, and AI approaches in order to enhance the predictability of outcomes in response to the dietary intervention. Image created with Biorender.com

Fig. 3

Diet contributes to the intertwined mechanisms between the microbiota and host that have yet to be fully elucidated [107]. The physical structure and chemical composition of dietary intake is a large effector of health; moreover, dietary nutrients that bypass host absorption and secretion support the activity of the gut microbiome [109], yet there remains a complex inter-change between multiple other components outside of these. Image created with Biorender.com