Translating the human microbiome - Nature

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Translating the human microbiome James Brown, Willem M de Vos, Peter S DiStefano, Joël Doré, Curtis Huttenhower, Rob Knight, Trevor D Lawley, Jeroen Raes & Peter Turnbaugh Nine experts discuss the challenges in translating current research on the human microbiome into strategies for disease prediction, diagnosis and therapy.

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ver the past decade, an explosion of descriptive analyses from initiatives, such as the Human Microbiome Project (HMP) and the MetaHIT project, have begun to delineate the human microbiome. Inhabitants of the intestinal tract, nasal passages, oral cavities, skin, gastrointestinal tract and urogenital tract have been identified using whole genome James Brown is director, computational biology, GlaxoSmithKline, Collegeville, Pennsylvania, USA; Willem M. de Vos is professor of microbiology, Wageningen University, Wageningen, Netherlands, and Finland Academy Professor, Helsinki University, Helsinki, Finland; Peter S. DiStefano is senior vice president, research & development, Second Genome, Inc., San Bruno, California, USA; Joël Doré is group leader at the Institut National de la Recherche Agronomique, Microbiologie de l’Alimentation au Service de la Santé Humaine, Paris, France; Curtis Huttenhower is at the Biostatistics Department, Harvard School of Public Health, Boston, Massachusetts, USA; Rob Knight is at the Department of Chemistry and Biochemistry, University of Colorado at Boulder, Boulder, Colorado, USA, and the Howard Hughes Medical Institute, Boulder, Colorado, USA; Trevor D. Lawley is at the Wellcome Sanger Trust Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK; Jeroen Raes is a group leader at VIB (Vlaams Instituut voor Biotechnologie) and professor at the Vrije Universiteit Brussel, Flanders, Belgium; and Peter Turnbaugh is at the Harvard FAS Center for Systems Biology, Cambridge, Massachusetts, USA. e-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]; [email protected]; [email protected]. edu; [email protected]; [email protected]

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sequencing, cultivation, metagenomics, metatranscriptomics, metaproteomics and metabolomics. Generation of these data has led to an improved understanding of the contribution of the human microbiome to physiology, health and disease. Nature Biotechnology approached several experts to seek their views on what steps need to be taken to move from descriptive microbiome biology to targeted therapies that tackle diseases in which microbiome dysfunction is a contributory factor.

Peter S. DiStefano: There continue to be many microorganisms uncovered in humans that need to be fully sequenced, annotated and banked. As these resources become more complete, it will become easier to query changes in microbiota relevant Peter S. DiStefano to health and disease.

How deep will we need to go in terms of sequencing depth and microbial characterization in each body niche?

Joël Doré: Let me start [by] noting that this is dependent on the depth of analysis because the deeper we go (more sequences per sample), the more diversity we find. The dominant human Joël Doré fecal microbiota (down to 1 per 1,000 of most dominant members) is already fairly well covered for populations of the Northern Hemisphere, but similar efforts are lacking for populations of South America, Africa and India, for example. The intestinal mucus layering the 300 square meters of gut epithelium in each individual has yet to be explored at the level of [the] metagenome. The presence of the epithelium (bearing human genes) and the access to this niche mainly via biopsies (invasive sampling process) is a major limitation towards [achieving] this challenging goal.

James Brown: I don’t see any limitations to the amount of DNA or RNA sequencing that will be needed, given the variability at the individual person level. As we move James Brown to more personalized medicine, the microbiome might be another area of deeper characterization for patient diagnosis. Also given that the microbiota within an individual varies over time, there will be [a] need for more frequent testing and monitoring. Willem M. de Vos: Saturation of the readers is likely to be reached earlier than saturation of the ecosystems as [the ecosystems] are highly personalized, quite diverse and differ at different depths—hence some more deep sequencing remains to be Willem M. de Vos done.

Curtis Huttenhower: Just as there’s no particular limit to the number of interesting biological conditions under which microarrays or RNAseq can be executed, there’s not any obvious ‘saturation point’ for metatranscriptomics. Sequencing rare organisms or genes will be better addressed by single-cell techniques than

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f e at u r e metagenomics, which is one way to preclude the need for ‘depth’ per se. [Ribosomal] 16S sequence catalogs for humanassociated communities are now fairly Curtis Huttenhower well saturated, especially with recent releases of catalogs like Greengenes; the HMP placed saturation of microbial genus detection in adult Western populations at about 90%, although there’s plenty of work to be done in similarly cataloging other populations. I would claim that reference genomes are the other main area in human microbiome studies that will provide the most benefit from increased saturation—only a few clades like Escherichia coli or Staphylococcus aureus have been sequenced in depth. Trevor D. Lawley: The gap now is in the compilation of reference genomes. Although we have [ribosomal] 16S and other sequence data, we will require culturing of bacteria Trevor D. Lawley and whole genome sequences to complement metagenomic analyses. Jeroen Raes: I think for the gut-encoded gene families, we are fairly close. In the first MetaHIT Nature paper [464, 59–65, 2010], the saturation curves were basically flat after sequencing the gut microbial DNA of 70 individuals [124 were sequenced in total]; now when we dig into other communities, we see an increase, but not that much. I think the aim for the gut should now be to sample many diverse phenotypes (diseases, populations, ages and so on). For the other niches, we’re still scratching the Jeroen Raes surface. Rob Knight: It depends on what hypothesis you want to test. There is no single answer. Peter Turnbaugh: In my opinion, the field is to a large degree moving away from purely descriptive surveys of who’s there and what genes are there, to a more in-depth appreciation

for the underlying ecological principles that shape these microbial communities. Just as we would never expect to photograph every tree in the forest, we don’t reasonably expect to sequence every bacterium in the world. The challenge is finding ways to find the important signals in all that Peter Turnbaugh noise. What are the biggest current technical or study-design roadblocks? R.K.: Shotgun metagenomics is really hard, we need either new algorithms or to move to single-cell (which is still limited by coverage) and/or microculture (which is Rob Knight very hard, especially for anaerobes). Also, too many studies look at associations, and not causation. J.B.: To understand the role of the microbiome in disease, we will need large well-designed studies for two reasons: first, the large heterogeneity of the microbiota communities, even across healthy individuals; and second, many chronic diseases are not well characterized and are likely multiple subtype syndromes. There is also a need to carefully integrate other metadata on patients, such as disease phenotype, medical history and so on. Can technology solve these issues? Possibly, but we need to have massive integration of data and the right analysis protocols. One key area for improvement is the need for more cause-effect experiments that will allow understanding of whether changes in the microbiome are truly responsible for disease initiation or progression or whether the changes in the bacterial communities are merely opportunistic. Here, the field is limited in that the academic community only has a few crude modulators of the microbiome, such as commercially available antibiotics, prebiotics and probiotics. However, precise modulators or ‘knockout/knock-in’ techniques could greatly enhance our understanding of microbiome-disease relationships. The field is so vast and complex that there will be the need for innovative collaborative initiatives between industry, academia and government.

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P.S.D.: Access to the right sets of biospecimens and [ways for] adequately powering studies remains challenging. It would be useful to have community-wide agreement on the use of standard reference materials to aid in assessing data quality and in comparison of results. T.D.L.: Culturing of microbiome bacteria is the biggest limitation. We need genome or DNA sequences and physiology of cultured members to fully understand the microbiome. Although many bacterial species are denoted as ‘unculturable’, I believe that with media tweaks and different processing of samples, it’s possible that we could cultivate all members of the microbiota. J.R.: I think efficient and consistent sample treatment is a major hurdle. There is still work to be done on standardized protocols and lab automatization to enable the field to move forward into large-scale clinical trials. Also, there is a lot of work to be done using bioinformatics to extract more information out of the sets of genes we obtain from metagenomic sequencing—there’s still treasure buried in all the publicly available data. J.D.: Identifying expressed genes, rather than cataloging the genes present, to move closer to a functional assessment at the level of the metatranscriptome is a challenge. Only a few laboratories are working on the preparation of representative RNA extracts that might tackle this problem. Identifying mechanisms and molecules detailing the crosstalk between commensal bacteria and human cells is another challenge. Metagenomic libraries of large fragments of gut microbial genomes have been prepared that allow such functional explorations. C.H.: I would contend that the biggest current roadblock is study design. We now know that sample sizes must be larger, such factors as caging and parental background can affect mice, early life matters and every body habitat is very different. Few of these factors have yet been taken into account to generate large translationally-focused data sets yielding high-quality data. P.T.: I think the biggest challenge is to establish mechanism. Koch’s postulates work well for single isolates, but are challenging, if not impossible, for more complex systems. New computational methods and experimental systems are helping to address some of these concerns, but in the end we may just have to accept an increased level of uncertainty prior to translating our findings to humans. 305

f e at u r e What are the limitations of computational analyses of metagenomic data?

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J.B.: DNA and transcriptomic sequencing as well as metabolomics platforms will generate more and more data that will be challenging from a computational capacity perspective. However, a greater challenge will be the integrated analysis of meta–data sets covering not only microbiome data but also host genetics and genomics, patient history, disease phenotype and so on. P.S.D.: The major shortcoming is not computational power, as cloud technologies have scaled to keep pace with demand. The limitation is the reference databases of bacterial genomes needed to properly match all the experimentally derived sequences. Thus, a push to isolate a greater diversity of reference bacteria is still needed. J.D.: Metagenomic data contains ‘genomic information’, that is, ensembles of genes that derive from the same bacterial genome in the initial sample; reconstruction of complete bacterial genomes from metagenomic data has so far remained a challenge. Metagenomic data contains all the elements to allow reconstruction of the metabolic framework of the intestinal community. Thus far, this potential has been untapped and the exploitation of information has been limited to the ‘taxonomic or phylogenetic’ meaning of the data. J.R.: One major challenge is the development of tools to enable better interpretation of the data. Clinicians new to the field, in particular, are in great need of user-friendly tools that allow the functional characterization of microbiota shifts and interpret the possible metabolic consequences. C.H.: Lack of microbial protein characterization. Few computational techniques treat genome annotation differently now that we have thousands of microbial genomes rather than tens, and this carries through into our ability to characterize protein function in communities. We can identify bugs and proteins fairly well—but we don’t know what most of those proteins do (over two-thirds in most communities) or how they interact. As a next step after that, we have no systems-level models of microbial interaction in communities either, particularly when [the communities are] strongly influenced by host metabolism and immunity. R.K.: We only identify common organisms, but even that is very computationally expensive, 306

difficult to do, often fragile or hard to set up on new systems, and inaccurate at all levels (assemblies, gene calling, functional assignment, phylogenetic assignment). There is a huge amount of work to be done here! P.T.: We’re really limited by our lack of knowledge about microbial metabolism, which means that each new genome or metagenome is only partially annotated. Solving this will require high-throughput ways to associate each gene with a given function, structural biology initiatives and an increased number of genetically tractable microorganisms relevant to the human microbiome. Has there been a shift in emphasis (from species identification) to metagenomic analyses to characterize the role of microbial communities in disease? J.B.: A range of technologies will be key to understanding microbiome communities in healthy and diseased populations. 16S ribosomal RNA sequencing tells us ‘who is there.’ Metagenomics and RNA sequencing address ‘what are they doing?’ From the pharma perspective, both pieces of information are important since one might wish to therapeutically target a particular bacterium, enzymes or host-microbial interaction. Metabolomics is also a crucial technology since it might lead to a better understanding of the particular molecules involved in inflammatory responses driving disease etiologies. W.M.d.V.: [What we’re talking about] is both about genes and gene products, but in many cases this relates to specific microbes and their lifestyles, which can be diagnosed by 16S rRNA and related diagnostic sequences. When we want to treat patients what we need is cultured organisms! J.R.: In my opinion, whole genome sequencing (WGS)-based metagenomics is more costly than 16S but more informative because only WGS will truly enable functional interpretation. Transit time is an issue with metatranscriptomics, as it is not clear yet whether the fecal transcriptome is representative of what was going on inside the intestinal tract several hours before. P.S.D.: To understand the mechanisms by which the microbiota influence human physiology, we need a comprehensive understanding of which microbes are there, which genes are being expressed, and which proteins

and metabolites are being produced to affect the ecosystem. J.D.: 16S RNA will remain insufficient to access functionalities. RNA-seq will become a standard when the preparation of pure RNA that is truly representative of complex communities can be obtained. C.H.: Both microbial membership and protein function are important, particularly when the former can be identified at a very specific level. Pathogenic and nonpathogenic E. coli strains differ by only a few genes, and these important strain-level differences occur not just in pathogenicity, but in basic metabolism and host interaction mechanisms. RNA-seq will be vital to determine how pan-genomes are expressed, at what time scales and in response to what stimuli. R.K.: 16S RNA (but we need new approaches to connect sequence information to function). RNA-seq is critical, but is technically difficult. Personally, I think the future will be 16S RNA plus RNA-seq plus microculture. But opinions vary. P.T.: I think that the field will likely move rapidly towards functional studies, as has been done in other fields following the availability of a suitable reference genome. This shift towards understanding the active component of the human microbiome can enable us to highlight members of the community that are responsive to a given substrate, as our recent paper in Cell [152, 39–50, 2013] demonstrates for drug resistance and metabolism. How useful are animal studies that aim to manipulate the microbiome? J.B.: Animal models will always have a role in academic biomedical research since there are many well-established disease models and genetic approaches. However, GlaxoSmithKline Pharmaceuticals is very much focused on minimizing our use of animal models, by looking to develop more predictive in vitro and cellular assays as well as seeking therapeutic opportunities that can be quickly and ethically tested in informative experimental medicine studies in humans. P.S.D.: As with any effort to discover new therapeutics in a given disease, having animal data that helps elucidate mechanisms and demonstrate efficacy is critical. Oftentimes, however, animal models are poor facsimiles of the disease in question. To this end, the microbiome field has taken advantage of gnotobiotic mice


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f e at u r e inoculated with human feces (for example) in an attempt to ‘humanize’ the mice. This may still not be the optimal model but it represents a valuable approach to creating useful models as we modulate the microbiome. In vitro assays that probe host-microbe and microbe-microbe interactions will be important precursors to animal experiments.

problematic. Experimental design is absolutely crucial for studies linking dysbiosis to disease, and validation of computational outcomes is also critical.

T.D.L.: Animal studies are useful, but we need [the] methods to standardize them between labs. There are important cage-to-cage effects that can impact on results obtained in mouse studies. Mouse studies are unlikely to be reproducible if only 5–10 mice are used. The elephant in the room is standardizing the microbiota. I am part of a consortium aiming to set standards for the use of germ-free mice to ensure that we really do have germ-free mice. If this works, we could then add synthetic microbiota—such as Altered Schaedler Flora, although [it] is not great as it doesn’t recapitulate the microbiota well—to determine effects of individual species and communities on physiology and disease.

J.D.: So far, case-control studies have dominated. They compare patients and healthy controls and the biomarkers that derive from such studies have no predictive value. It is essential that longitudinal studies be implemented so as to allow the identification of predictive biomarkers for risk of disease onset, risk of aggravation in chronic disorders, or even to predict responders/nonresponders to treatments or nutritional supplementations or dietary restrictions.

J.R.: Animal studies are essential for causality research. The question is ‘what is the right model?’ Mice may be too distant from humans; there is more and more talk of pigs as a more suitable model. C.H.: We know very little about microbiome causality in humans because it’s near-impossible to control all relevant stimuli, to manipulate them in real time or to influence microbial acquisition early in life—so animal models are very important. Knock-in and knockout experiments have been central in genetics for decades but microbiome studies have seen almost no knock-in or knockout equivalents due to the lack of easily manipulated models. What about the use of the microbiome in biomarker research and in disease predisposition? J.B.: The microbiome could be a biomarker for disease status as well as drug efficacy and personalized medicine. Our understanding is not there yet, but for certain diseases, the microbiome status [of each patient] might be informative about the types of medicines (or their regimes) to be prescribed. T.D.L.: Proper statistical powering of microbiome studies is extremely difficult. The knowledge is not there to do this, which means that although there is a depth of sequencing data, correlating [it] with patient outcomes is very

W.M.d.V.: We have to be a bit modest as we have no real biomarkers yet—concepts, however, are developing.

C.H.: Gene expression and genetic association studies have demonstrated the statistical difficulty of discovering reproducible signals in high-dimensional data and the practical difficulty of finding large enough effect sizes to be clinically useful. Microbiome studies could benefit from these cautions toward methodological rigor and away from overoptimism. R.K.: The question is how not to make the same mistakes that were already made in microarrays, proteomics and other large-scale technologies. Much more communication is needed. Benchmarking efforts were critical in these other fields and are probably critical here but there has been very little support from funding agencies or journals. P.T.: I think a major goal is to identify the responsible genes for a given link between microbes and health, which then might be used in diagnostics or a novel drug target. Given the extent of horizontal gene transfer and intraspecies variation in the human microbiome, these genetic biomarkers may prove more fruitful than just measuring the abundance of a particular taxa. What kinds of studies are needed to advance therapeutic prospects? J.B.: I believe there will an emerging new paradigm in therapeutics. Traditionally, infectious disease and human chronic disease disciplines have been distinct, separate, with few cross-communication exchanges. However, recent studies have shown not only how the microbiome might impact chronic diseases like diabetes, obesity and asthma, but also that many pathogens depend on hijacking host proteins and pathways for their proliferation and

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viability. Thus, we might see more chronic disease therapeutics aimed at microbial species and communities while some viral diseases, as an example, might be treated by the inhibition of specific host pathways. Again, we need to understand the interactions between host and symbiont, or host and pathogen, then show that specific targeting of those interactions resolve the disease symptoms, with strong, supportive clinical evidence. P.S.D.: Therapeutic breakthroughs can be made by focusing on how the microbiota interacts with itself and with its human host to impact health and disease. This is demonstrated by the successful attempts to recapitulate the effects of fecal microbiome transplants with a small number of bacterial strains in rodents. This work broadly suggests that re-introduction of the correct composition of microbes can override microbial imbalances, or dysbiosis, implying that a ‘bugs as drugs’ approach may be broadly applicable. When fully sequenced, the total number of genes associated with the human microbiome could exceed the number of human genes by a factor of 100 to 1. So more broadly, characterization of the human microbiome opens up an enormous wealth of new drug targets for small molecules or other bioactives. Work aimed at connecting host biology with microbial gene regulation and secretory and metabolite production will be particularly insightful. Lastly, the development of novel therapeutics that modulate host factors at the intersection of the response to commensal or pathogenic microbes, including inflammatory pathways and epithelial barriers, may be a uniquely powerful approach. T.D.L.: We need studies focused on developing methods to rationally select bacterial candidates for a ‘bacteriotherapy’ type approach. We favor a nonbiased approach to find therapeutic bugs that will trigger a shift to a healthy profile in the disease-affected niche. J.R.: The potential for gut microbiota manipulation is enormous, and so is the market. In 15 years, we will all be drinking specific, personalized probiotic cocktails. I suggest that every healthy person freezes a fecal sample now so they will be able to treat themselves in the future. Also, manipulation at early stages of life will be crucial. The next studies that are necessary are twofold: we should urgently move to longitudinal studies (to get a grip on dynamics and dynamic interactions and show the predictive power of the biomarkers that are now starting to be identified) and properly controlled and carefully monitored intervention studies. 307

f e at u r e ing the microbiome will require discovery of microbial control points and the means to target them. W.M.d.V.: As well as cultured organisms, we also need robust clinical trials of potential therapies, for example, see our recent transplantation work with patients in Gastroenterology [143, 913–916, 2012] and NEJM [368, 407–415 (2013)]. R.K.: We need more animal models, more work on understanding the ecology of natural and designed communities, and more highthroughput screening to understand what drugs do [to] the vast unculturable majority of our microbes, not just the handful of mostly

Gram-negative pathogens they are usually tested against. P.T.: There’s been lots of progress recently on this, but we still know very little about how best to remove or introduce individual bacteria into a given microbial community. A lot more work needs to be done to develop targeted therapies and to understand what determines the degree of resistance to a given therapeutic or dietary intervention. Furthermore, it’s important to consider how gut microorganisms might shape our response to drugs that are meant to target the human, by modifying their efficacy or toxicity. We need to learn more about who’s responsible for these chemical biotransformations and which genes are required.

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C.H.: Designer probiotics and targeted interventions will be possible, but extremely difficult, for the same reasons that molecular therapies for cancer have proven challenging. An example like cancer, where we now know many of the mechanisms and proteins involved, represents a system that has evolved to be stable. A tumor represents a “community” of cells that specifically evolved to evade natural control mechanisms. The human microbiome has likewise evolved in each of us to reach a stable state that will be correspondingly difficult to perturb. The most successful current cancer treatments often involve very specifically targeted ‘one-two punches’ that hit exactly the right few control points to disrupt a stable state, and modify-

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