Throughout human existence, we have devised ways to use microorganisms to our benefit, involving them in food production, waste treatment and more. We have also been painfully aware of the negative consequences brought about by an unwanted microbial infection. However, most microorganisms associated with our bodies are not the cause of disease. As this fact became increasingly evident throughout the second half of the twentieth century, we have considered the role our commensal microbial communities have in regulating our health. We started asking questions about the ‘good guys’: who are they, what are they doing and how do they keep us healthy? Obtaining answers was closely linked to technological development: initially culturing anaerobes, then using germ-free animals to establish causal relationships and, later, in the form of sequence-based identification of microorganisms in the microbiota community. As sequencing became cheaper and analysis pipelines were developed to analyse complex communities, the idea of trying to identify what is ‘normal’ across large human populations took hold. This is quite an undertaking and led to the development of multi-million dollar projects, such as the Human Microbiome Project (HMP)1 and Metagenomics of the Human Intestinal Tract (MetaHIT). These projects have analysed, in excruciating detail, the structure, function and stability of thousands of human-associated microbial community samples. The result is a unique insight into the human–microorganism world that could revolutionize our approach to healthcare.
‘Normal’ is individual
One of the key findings from these projects is that, in terms of our microbial taxonomy, everyone is different. In healthy adults, an individual’s metagenomic profile is unique but also stable over time, relative to the whole population2,3, helping us explain how and why we respond differently to environmental change or clinical treatment. Inter-individual variation in microbial communities appears to be most related to factors such as host genetics, ethnicity and diet3; the causative pathways that lead to these differences remain a topic of investigation. Nevertheless, the spectrum of possible community compositions does not appear to be continuous, as there might be a limited number of well-balanced, stable host–microbial symbiotic states, that have been coined ‘enterotypes’4. By contrast, the functional capacity of human-associated microbial communities is well conserved across healthy human adults5. Despite taxonomic differences, the functional capacity of human-associated microorganisms is evenly diverse throughout a population, tailored to their host-associated environment3,5. We are now also beginning to appreciate the importance of microorganisms other than bacteria. It turns out that our feet, for example, are hotspots for high fungal diversity — a feature conserved across individuals, unlike bacteria6. The functional role of fungi, archaea and viruses remains a key area for continued research effort.
Poor health cannot hide
By gaining a population-scale insight into the ‘normal’ human–microorganism state, we can now confidently identify differences between healthy and unhealthy adults5,7. This is typically characterised by a reduction in microbial richness — a feature that we now know places us at higher risk of developing metabolic diseases, such as obesity, type-2 diabetes and inflammatory bowel disease (IBD). By elucidating a causative link between gut microbial communities and obesity, researchers and clinicians have opened up opportunities for innovative microbial-based treatment methods.
On the brink of a health revolution?
Population-scale projects such as HMP and MetaHIT have begun to transform our understanding of human health. Relationships between microbial diversity and key physiological or environmental metrics have provided tantalising evidence that our health is intimately linked to the microorganisms living in and on us. Causative pathways are more difficult to define but are sure to emerge in the coming years. Indeed, the next phase of HMP (the Integrative Human Microbiome Project) specifically focuses on pregnancy and pre-term birth, IBD, and the onset of type-2 diabetes, aiming to longitudinally follow large cohorts using multi-omic technologies to determine the changes that are associated with developing disease states, with the hope of identifying early signatures of disease and of starting to elucidate disease mechanisms. In Europe, Horizon 2020 also funded three large projects focused on microbiome characterization of particular diseases: late-stage liver disease, cancer and autism. The goal is to enable a more personalised approach to medicine and nutrition, rather than relying on traditional ‘one-size-fits-all’ treatments. Initial studies into personalised nutrition have shown promising results — with the right food, people feel better and recover healthy levels of gut bacterial richness. With ever-declining costs for DNA/RNA sequencing, the concept of profiling individuals and tailoring nutritional advice and treatment plans may no longer be in the realm of science fiction.
These early large population-scale studies have created a lasting legacy. The sheer volume of data attained by these projects has necessitated innovations in data science, such as those outlines in refs8,9,10 — analytical pipelines that can be translated to other ‘big data’ applications. The success of these large-scale projects, in terms of scientific innovation, knowledge insight and the potential for innovating healthcare, has also inspired other regions to follow suit. Most recently, India has announced an intention to launch its own HMP project11. We are, perhaps, more acutely aware of our microbiome than ever before, but the continued need for such large-scale research exemplifies how far we have to go to fully understand the life we share with our microorganisms.
Human Microbiome Project Consortium. A framework for human microbiome research. Nature 486, 215–221 (2012).
Schloissnig, S. et al. Genomic variation landscape of the human gut microbiome. Nature 493, 45–50 (2013).
Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).
Costea, P. I. et al. Enterotypes in the landscape of gut microbial community composition. Nat. Microbiol. 3, 8–16 (2018).
Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010).
Findley, K. et al. Topographic diversity of fungal and bacterial communities in human skin. Nature 498, 367–370 (2013).
Le Chatelier E. et al. Richness of human gut microbiome correlates with metabolic markers. Nature 500, 541–546 (2013).
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).
Segata, N. et al. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat. Methods 9, 811–814 (2012).
Pedersen, H. K. et al. A computational framework to integrate high-throughput ‘-omics’ datasets for the identification of potential mechanistic links. Nat. Protocols 13, 2781–2800 (2018).
Seetharaman, G. India gears up for Rs 150 core microbiome project to uncover links to diseases. The Economic Times (6 January 2019).