The human gut microbiota harbors a heterogeneous and dynamic community of microorganisms that coexist with the host to exert a marked influence on human physiology and health. Throughout the lifespan, diet can shape the composition and diversity of the members of the gut microbiota by determining the microorganisms that will colonize, persist, or become extinct. This is no more pronounced than during early-life succession of the gut microbiome when food type and source changes relatively often and food preferences are established, which is largely determined by geographic location and the customs and cultural practices of that environment. These dietary selection pressures continue throughout life, as society has become increasingly mobile and as we consume new foods to which we have had no previous exposure. Dietary selection pressures also come in the form of overall reduction or excess such as with the growing problems of food insecurity (lack of food) as well as of dietary obesity (overconsumption). These are well-documented forms of dietary selection pressures that have profound impact on the gut microbiota that ultimately may contribute to or worsen disease. However, diets and dietary components can also be used to promote healthy microbial functions in the gut, which will require tailored approaches taking into account an individual's personal history and doing away with one-size-fits-all nutrition. Herein, we summarize current knowledge on major dietary selection pressures that influence gut microbiota structure and function across and within populations, and discuss both the potential of personalized dietary solutions to health and disease and the challenges of implementation.

Chronic dietary protein-restriction can create essential amino acid deficiencies and induce metabolic adaptation through the hepatic FGF21 pathway which serves to maintain host fitness during prolonged states of nutritional imbalance. Similarly, the gut microbiome undergoes metabolic adaptations when dietary nutrients are added or withdrawn. Here we confirm previous reports that dietary protein-restriction triggers the hepatic FGF21 adaptive metabolic pathway and further demonstrate that this response is mediated by the gut microbiome and can be tuned through dietary supplementation of fibers that alter the gut microbiome. In the absence of a gut microbiome, we discover that FGF21 is de-sensitized to the effect of protein-restriction. These data suggest that host-intrinsic adaptive pathways to chronic dietary protein-restriction, such as the hepatic FGF21 pathway, may in-fact be responding first to adaptive metabolic changes in the gut microbiome.

Asthma is the most common chronic disease within the paediatric population. Although it is multifactorial, its onset may be linked to early-life exposures with subsequent impact on immune system development. Microbial and dietary metabolic products have been implicated in the development and exacerbation of paediatric asthma. Linoleic acid is the most common omega-6 polyunsaturated fatty acid in the Western diet. In this review, we summarise the literature regarding the involvement of linoleic acid in the development of and its impact on existing paediatric asthma. First, we summarise the existing knowledge surrounding the relationship between human microbial metabolism and allergic diseases in children. Next, we examine cellular or animal model-based mechanistic studies that investigated the impact of dietary- and microbial-derived linoleic acid metabolites on asthma. Finally, we review the literature investigating the impact of linoleic acid metabolites on the development and exacerbation of childhood asthma. While there is conflicting evidence, there is growing support for a role of linoleic acid in the onset and pathophysiology of asthma. We recommend that additional cellular, animal, and longitudinal studies are performed that target linoleic acid and its metabolites.

The relationship between microbiota, short chain fatty acids (SCFAs), and obesity remains enigmatic. We employ amplicon sequencing and targeted metabolomics in a large (n = 1904) African origin cohort from Ghana, South Africa, Jamaica, Seychelles, and the US. Microbiota diversity and fecal SCFAs are greatest in Ghanaians, and lowest in Americans, representing each end of the urbanization spectrum. Obesity is significantly associated with a reduction in SCFA concentration, microbial diversity, and SCFA synthesizing bacteria, with country of origin being the strongest explanatory factor. Diabetes, glucose state, hypertension, obesity, and sex can be accurately predicted from the global microbiota, but when analyzed at the level of country, predictive accuracy is only universally maintained for sex. Diabetes, glucose, and hypertension are only predictive in certain low-income countries. Our findings suggest that adiposity-related microbiota differences differ between low-to-middle-income compared to high-income countries. Further investigation is needed to determine the factors driving this association.

Background

SARS-CoV-2 is an RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Viruses exist in complex microbial environments, and recent studies have revealed both synergistic and antagonistic effects of specific bacterial taxa on viral prevalence and infectivity. We set out to test whether specific bacterial communities predict SARS-CoV-2 occurrence in a hospital setting.

Methods

We collected 972 samples from hospitalized patients with COVID-19, their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and used these bacterial profiles to classify SARS-CoV-2 RNA detection with a random forest model.

Results

Sixteen percent of surfaces from COVID-19 patient rooms had detectable SARS-CoV-2 RNA, although infectivity was not assessed. The highest prevalence was in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples more closely resembled the patient microbiome compared to floor samples, SARS-CoV-2 RNA was detected less often in bed rail samples (11%). SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity in both human and surface samples and higher biomass in floor samples. 16S microbial community profiles enabled high classifier accuracy for SARS-CoV-2 status in not only nares, but also forehead, stool, and floor samples. Across these distinct microbial profiles, a single amplicon sequence variant from the genus Rothia strongly predicted SARS-CoV-2 presence across sample types, with greater prevalence in positive surface and human samples, even when compared to samples from patients in other intensive care units prior to the COVID-19 pandemic.

Conclusions

These results contextualize the vast diversity of microbial niches where SARS-CoV-2 RNA is detected and identify specific bacterial taxa that associate with the viral RNA prevalence both in the host and hospital environment. Video Abstract.