Assessing the human gut microbiota in metabolic diseases

Fredrik Karlsson, Valentina Tremaroli, Jens Nielsen, Fredrik Bäckhed, Fredrik Karlsson, Valentina Tremaroli, Jens Nielsen, Fredrik Bäckhed

Abstract

Recent findings have demonstrated that the gut microbiome complements our human genome with at least 100-fold more genes. In contrast to our Homo sapiens-derived genes, the microbiome is much more plastic, and its composition changes with age and diet, among other factors. An altered gut microbiota has been associated with several diseases, including obesity and diabetes, but the mechanisms involved remain elusive. Here we discuss factors that affect the gut microbiome, how the gut microbiome may contribute to metabolic diseases, and how to study the gut microbiome. Next-generation sequencing and development of software packages have led to the development of large-scale sequencing efforts to catalog the human microbiome. Furthermore, the use of genetically engineered gnotobiotic mouse models may increase our understanding of mechanisms by which the gut microbiome modulates host metabolism. A combination of classical microbiology, sequencing, and animal experiments may provide further insights into how the gut microbiota affect host metabolism and physiology.

Figures

FIG. 1.
FIG. 1.
Methods for studying the microbiota. Traditionally, microbial communities have been characterized by culturing on specific plates, but this is only amenable to the culturable fraction of the members (20–50% [84,86]) and has limited resolution. Culture-independent methods based on characterization of the 16S rRNA genes have been developed and also provide information for organisms that cannot be cultured. Shotgun sequencing of the whole genome provides information about the functional and metabolic potential of the community.
FIG. 2.
FIG. 2.
In the bioinformatic pipeline for analysis of whole metagenome shotgun sequences, sequences are subjected to quality control by removing uncertain base calls and contaminant sequences. Alignment of sequence reads to reference genomes is used for calculating species abundance. De novo assembly is used to identify genes not present in public databases. Genes can be functionally annotated and mapped onto metabolic networks such as in KEGG. Abundance of genes and species are compared among groups, and associations with disease can be tested.
FIG. 3.
FIG. 3.
Germ-free mice can be used to study the effect of a gut microbiota on its host. Colonization of germ-free mice with human microbiota from different donors can test if there are functional differences between communities. Colonization of germ-free mice also allows investigation of the interaction between the microbiota and specific diets. Synthetic microbiota are defined communities with known species composition and provide a controlled environment for testing the interaction of microbes with diet and host.

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