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, 489 (7415), 220-30

Diversity, Stability and Resilience of the Human Gut Microbiota


Diversity, Stability and Resilience of the Human Gut Microbiota

Catherine A Lozupone et al. Nature.


Trillions of microbes inhabit the human intestine, forming a complex ecological community that influences normal physiology and susceptibility to disease through its collective metabolic activities and host interactions. Understanding the factors that underlie changes in the composition and function of the gut microbiota will aid in the design of therapies that target it. This goal is formidable. The gut microbiota is immensely diverse, varies between individuals and can fluctuate over time - especially during disease and early development. Viewing the microbiota from an ecological perspective could provide insight into how to promote health by targeting this microbial community in clinical treatments.


Fig. 1
Fig. 1. Maintaining our gut microbial lawn
Maintaining a healthy microbiota is in some ways like lawn care: severe interventions like antibiotics can take the ecosystem back to bare earth, requiring it to be re-established from scratch. Although many people recover naturally, it is by no means guaranteed, and “weedy” species that are adapted to perturbed ecosystems often run wild. In this review, we discuss several current strategies for ecosystem restoration: probiotics (re-seeding with a few well-defined “good microbes”), prebiotics (adding compounds that are thought to specifically promote the growth of beneficial microbes), and fecal bacteriotherapy (transplanting the entire microbial ecosystem, e.g. from a stool sample). These strategies are analogous to using lawn seed, turf food, and sod respectively. An additional strategy, not shown, is to use specific drugs that target undesirable members of the microbial community such as narrow-spectrum antibiotics. Although we are beginning to learn what a healthy microbial community looks like and to recognize signs of weeds, our understanding of which strategies for altering the microbiota work best, and predicting which will work for a given individual, is still in its infancy.
Fig. 2
Fig. 2. Tools for understanding compositional and functional diversity of the microbiota, and for generating hypotheses about functionally important genes and how to modulate metabolic phenotypes
Extracted DNA from fecal samples can be assessed using targeted sequencing of a phylogenetically informative gene (usually SSU rRNA) or random sequencing of all genes. Genome sequences from cultured isolates link these two datasets by indicating which species contain which genes, and therefore functions. Shotgun metagenomic data is thus substantially more useful as the number of reference genomes continues to increase with additional strain sequencing efforts. SSU rRNA gene sequences are usefully related to each other in phylogenetic trees, because related phylotypes (clusters of similar sequences defined by sequence similarity) generally have more similar functional attributes. Functional genes can be binned into functional categories (FC) that are a part of a functional ontology, but those encoding proteins that perform known enzymatic reactions are most usefully related to each other using metabolic networks, because genes that are adjacent in a particular metabolic pathway can produce a phenotype in concert with each other. Compositional and functional diversity patterns can inform each other. They are often highly correlated, but cases where these general correlations do not hold can be biologically or ecologically important. Predicting functions from the species assemblage present still remains an unsolved problem, although the fact that overall genome differences are highly correlated with differences in the SSU rRNA sequence suggests that such predictions may one day be possible. To date, the most powerful studies tend to combine SSU rRNA profiling to determine taxon abundance (the microbiota) with shotgun metagenomic profiling to understand the functions present (the microbiome). Supplementing these studies with mRNA, protein and metabolite level analyses of community samples (and of concurrently obtained host specimens, such as serum and urine) will be crucial so that we can move from in silico predictions of function to direct measurements of expressed community properties.
Fig. 3
Fig. 3. Diversity of the human microbiota at different phylogenetic scales
The human microbiota displays a remarkable degree of variation within and between individuals. Although this complexity can be simplified by evaluating communities at higher taxonomic levels, such as comparing relative abundances of phyla, the many species within each phylum have different biological properties, and significant changes detected at higher taxonomic levels are likely driven by only a subset of the species in those higher taxa. Here we illustrate the high diversity and variability among individuals, and the degree to which taxonomic grouping at high levels can mask this diversity, using 16S rRNA sequence data from four of the US adults previously described in ref. . We chose these four individuals to illustrate how phylum level diversity can vary dramatically even across healthy adults in the same population. Individual A has an unusually high proportion of Bacteroidetes, individual D unusually high Fusobacteria, and individuals B and C have more typical phylum level distributions for this cohort, dominated by Firmicutes and Bacteroidetes. However, even the apparently similar B and C differ at finer scales. The tree depicts the phylogenetic relationships between species-level phylotypes in just the Firmicutes phylum, by far the most diverse of the phyla, in individuals B and C. Branches specific to individual B are red, branches specific to individual C are blue, and shared branches are purple. Each individual has many unique phylotypes not found in the other. As described in many surveys of the human gut ,,, the Ruminococcaceae and Lachnospiraceae families are particularly rich in phylotypes.
Fig. 4
Fig. 4. Functional redundancy
Microbial ecosystems exhibit a high degree of functional redundancy in microbial ecosystems may mirror that in macroecosystems. The HMP dataset illustrates this principle: oral communities (a) and fecal communities (b) show tremendous diversity in species abundance, yet remarkable similarities to one another in functional profiles obtained by shotgun metagenomics from the same samples (c) and (d) respectively.
Fig. 5
Fig. 5. Human microbial diversity and “enterotypes”
The reported “enterotypes” were determined when evaluating only individuals from the US and Europe, yet including children from the US and children and adults from developing countries greatly expands the picture of human-associated microbiota diversity. We illustrate this here by showing the relationship between the microbiota of 531 healthy infants, children, and adults from Malawi, Venezuelan Amerindians, and the US that were evaluated using sequences from the 16S rRNA gene in fecal samples and a PCoA analysis of unweighted UniFrac distances (adapted from ref. Fig. S2). Microbiota diversity is explained primarily by age (with infants differentiating strongly from adults) and next by culture (with adults from the US having distinct composition compared to adults from Malawi and Venezuelan Amerindians). The points from Western adults are circled in white, and the rest are shaded in blue.
Fig. 6
Fig. 6. Compositional transitions in the human gut microbiota
During early development, the gut microbiota undergoes a systematic turnover of species (primary succession) until a stable adult state is reached. Positive and negative feedback loops likely play a role both in driving primary succession and in conferring resilience to healthy stable equilibrium states. Acute disturbances, such as antibiotic administration, generally are followed by an unstable state that progresses to a stable state through a process of secondary succession. In some cases, the stable state that returns highly resembles the pre-disturbance state, indicating a complete recovery, but sometimes the post-recovery stable state is distinct. Post-disturbance stable states may be both degraded and resilient, for instance as suggested the persistence of post-infectious irritable bowel syndrome (i.e. IBS that forms after an initial acute disturbance of the microbiota from an enteropathogen) in some individuals for years and even decades . Resilience of degraded states is likely driven by unique positive and negative feedbacks that occur both in concert with and independent of the host. Degradation to a stable state may also occur as a result of persistent stressors, such as poor diet, that slowly degrade resilience of a healthy state until a threshold is passed such that new feedbacks become important in maintaining community composition and stability. Developing therapies that encourage transition from degraded to healthy stable states, or complete recovery to a healthy stable state following disturbance, may involve identifying the species (or species combinations) and processes that are key drivers of these feedbacks. One critical unresolved question is whether interventions are more effective early in succession when communities are more unstable but may be stochastic, or later in succession when convergence to the end point is more certain but the trajectory may be more difficult to change.

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