The microbiota of a typical, healthy human contains 10 times as many cells as the human body and incorporates bacteria, viruses, archea, protozoans, and fungi. This diverse microbiome (the collective genomes of the microbial symbionts that inhabit a human host) is essential for human functioning. We discuss the unstated assumptions and implications of current conceptualizations of human microbiota: (1) a single unit that interacts with the host and the external environment; a multicelled organ; (2) an assemblage of multiple taxa, but considered as a single unit in its interactions with the host; (3) an assemblage of multiple taxa, which each interacts with the host and the environment independently; and (4) a dynamic ecological community consisting of multiple taxa each potentially interacting with each other, the host, and the environment. Each conceptualization leads to different predictions, methodologies, and research strategies.
1. Introduction
The scientific
community has just begun to appreciate the number and complexity of organisms
inhabiting the human body. The human microbiota contains 10 times as many cells
as the human body and incorporates bacteria, viruses, archea, protozoans, and
fungi. Many essential body processes require the presence of these diverse
microorganisms to maintain pH in the oral and vaginal cavities, prevent invasion
by pathogenic organisms, stimulate the immune system, aid digestion, and provide
nutrients essential to our health. If a diverse microbiota is essential for
human functioning [1], disruption of the normal
microbiota should have significant negative consequences for human health.
Indeed, studies suggest that the gut microbiota can influence risk of obesity
[2], inflammatory bowel disease [3], cardiovascular disease [4, 5], and allergies
and asthma [6].
The National Institutes
of Health recently launched a series of initiatives focused on characterizing the
human microbiome, the collective genomes of the microbial symbionts that
inhabit a human host. Characterizing the microbiome provides insight into the
diversity of genomes inhabiting the human host and is a first step towards
understanding the complicated interactions among symbionts and between the
symbionts and the human host. This launch has stimulated much discussion on why and how
the human microbiome should be characterized. There has been little explicit
discussion, however, of the underlying conceptualizations or models of the microbiota
which might guide this characterization. Models provide a framework for designing
experiments and for making inferences and predictions. In this commentary, we describe the range of conceptualizations
of the human microbiota that have been implicit in different segments of this
emerging literature. By making explicit the underlying models, we reveal the
underlying assumptions and can consider the strengths and weaknesses of the
different models in fitting existing observations, identify important data
gaps, make predictions, and consider what model best applies in a given
situation or for a given research or clinical question.
Figure 1 graphically
displays the range of conceptualizations of the microbiota implicitly described
in the following literature.
Figure 1: Four conceptualizations of human microbiota that focus to varying
degrees on structure and/or function of the microbiota as a whole or
of the component microbial taxa. Assumptions and implications of
the extremes of simplicity and tractability on one hand (the
multicelled organ conceptualization, Figure
1(a)) and complexity and
relative intractability (the dynamic ecological community
conceptualization, Figure
1(d)) are described in Table
1. All the interactions (linking arrows)
are mediated to some extent by changes in the internal environment,
which is not shown to enhance clarity. Mechanisms underlying the
various interactions, including the role of internal environment,
are depicted in Figure
2.
(1)The microbiota
considered as a single unit that interacts with the host and the external environment;
a multicelled organ.(2)The microbiota
consisting of multiple taxa, but considered as a single unit in its
interactions with the host.(3)The microbiota
as an assemblage of multiple taxa, which each can interact with the host and
the environment independently.(4)The microbiota
as a dynamic ecological community consisting of multiple taxa each potentially interacting
with each other, the host, and the environment.
Conceptualizations (1) and (4) are clearly extremes and
most research probably falls somewhere between them. However, because they are
extremes, we can more clearly contrast them and their underlying assumptions,
which have different implications for the development of clinical interventions
(see Table 1). We expect an understanding of the human microbiota to require a
melding of conceptualizations and associated theories before the promise of
translating this understanding to new prevention, diagnostic, and treatment
strategies can be achieved.
Table 1: Underlying assumptions of conceptualizing
human microbiota as a multicelled organ versus an ecological community. Some
of the assumptions of the multicelled organ conceptualization also apply to
the intermediate conceptualizations depicted in Figure
1.
2. The Microbiota as a Multicelled Organ
The microbiota is implicitly
assumed to be much like a multicelled organ in much of the medical literature
(Table 1) [2]: like an organ, a healthy microbiota consumes, stores, and
redistributes energy and mediates important chemical transformations that benefit
the host [7]. Communication among the cells that make up the microbiota enables
replication and repair, and a set of feedback loops link host and microbiota (Figure 1(a)). The focus of an organ conceptualization is on function, with metabolic products and immune or neurological
responses depending on the microbiota as a whole [7].
This view also implicitly assigns borders to the unit of interest, assuming
that each spatially defined set of microbiota—the gut, oral community, or vaginal community—exists as a
distinct and independent entity, and that each entity interacts with the host
and the external environment as a single unit. Perhaps most importantly, this
conceptualization assumes that any variation in the microbiota over time and
between individual hosts is not functionally important or can be overlooked because
of redundancies in genetic elements encoding various metabolic pathways in
different strains or species. These unstated assumptions, summarized in Table 1, have the advantage of simplifying the system and focusing our attention on
measuring inputs and outputs, physical structure, and defining spatial
boundaries.
Conceptualizing the microbiota
as an organ suggests research should characterize the range of inputs and
outputs and immune response to the outputs and correlate them with healthy and
diseased states for development of diagnostics. This conceptualization also
implies that a therapeutic that adjusts the inputs and outputs could return the
organ to a healthy state or substitute for a poorly functioning organ. For example, early diabetes—a malfunctioning pancreas—is diagnosed by measuring organ inputs (glucose levels), and is treated by decreasing inputs (lowering glucose levels) or
supplying output (insulin). We might envision similar inputs and outputs that
can be used to diagnose and correct disrupted microbiota in the skin, mouth,
gut, or vaginal cavity.
Assuming a physical
structure and boundaries stimulates studies to explore that structure and
define boundaries. For example, conceptualizing the microbiota as an organ leads us to consider that the microbiota on the skin or intestinal lumen might form physical structures, such as biofilms. This structure might vary in size and composition, being a thick lawn in some
areas and thin islands in others and act as an additional physical barrier to
colonization by pathogens. Disrupting these
protective biofilms chemically or physically may lead to invasion by
pathogens. Additionally, the size or
denseness of the structure might in some surfaces be associated with disease. Assuming
a defined boundary suggests that microbiota might be moved or be removed, and
that there are optimal areas for measuring inputs and outputs. These are all
testable hypotheses. The disadvantage of
conceptualizing the microbiota
as an organ is that it necessarily minimizes the complexity of a diverse
microbiota, which may lead us to either underestimate the possible unintended
consequences or overestimate the potential of proposed interventions.
The current research
focus on cataloging the diversity of microbiota using genomic techniques [8] takes a step beyond viewing the microbiota as a single,
homogeneous unit (Figure 1(b)). While a
critical next step, this approach goes no
further than the basic organ-view in understanding the mechanisms that drive variation in function of the microbiota; the
underlying assumptions and implications of this approach remain quite similar to
those of the “microbiota as organ” conceptualization (Table 1).
3. Microbiota as an Ecological Community
The other extreme is to conceptualize the microbiota as a continuum
of dynamic ecological communities living in the numerous microhabitats of the
human body [9]. Each species or strain of the microbiota interacts with other
members of the microbiota and with the host, as well as with the external
environment (Figure 1(d)). This conceptualization highlights interactions
between component organisms and their dynamics; a dynamic and spatially
continuous system is assumed, and the net effects can be positive, negative, or
neutral towards the host (Table 1). Key to
this conceptualization is that understanding the underlying processes that
control community structure, including the interactions among the microbiota
themselves, is essential for understanding its function. This conceptualization
has the advantage of increased realism, but is much more complex and
consequently may be less useful for some purposes.
Considering microbiota as an ecological community
stimulates research into how that community reacts to insults. For example, a
number of conditions, such as reactive arthritis, occur in some individuals in
response to infection. One current theory is that certain microbial surface
antigens mimic host cell receptors, so individuals with a particular variant in
immune signals generate an immune response to their own cells after infection
has cleared. The role of microbiota in
mediating this response has not yet been considered. However, we know that the gut
microbiota is important in modulating host immune response [2]. It is possible
that bacteria that lead to reactive arthritis disrupt the signals between the
human body and the microbiota such that the immune system no longer sees
organisms with antigens similar to those of the host as self, leading to self-attack.
Consequently, the reason that reactive arthritis is frequently self-limiting may
be related to restoration of the normal microbiota with subsequent restoration
of immune signals.
While some research has conceptualized the human microbiota
as an ecological community, the interactions among microbiota remain almost
completely unexplored [10]. Most work is similar to the conceptualization in
Figure 1(c), characterized by independent relationships between each member of
the microbiota and its human host, but not among the microbiota themselves [5]. However, we
suspect that interactions among members of a community, including the numerous
indirect pathways of influence generated in such webs, are integral to understanding
the dynamic and spatially heterogeneous nature of many aspects of the human
microbiota and, therefore, to the functioning of those communities [11–13]. If so,
however, complex and difficult, research must address how this understanding of
ecological dynamics and function can be translated to successful clinical
interventions.
4. Research and Clinical Consequences of Alternative Conceptualizations of the Human Microbiota
The underlying conceptualization of the microbiota guides,
either explicitly or implicitly, medical approaches to treating and preventing
conditions of disrupted flora. An organ view assumes that switching from an
unhealthy (dysfunctional) to a healthy (functional) state can be achieved by manipulating
inputs or outputs. With this model in mind, the associated research agenda will
focus on characterizing the products of the microbiota, their healthy and
diseased ranges, and how the products are affected by host characteristics and
the external environment (Figure 2). Therapeutic
studies will seek to shift metabolic products or cell signals back to the functional
state associated with health.
Figure 2: Potential mechanisms of interactions between external
environment, host and the microbiota in the multicelled organ
conceptualization of human microbiota.
By contrast, if we conceptualize the microbiota as multiple
communities of interacting genomes, we might instead try to reestablish or
maintain a specific microbial community structure associated with health. Success
of this approach depends on reestablishing a healthy microbial community, with
all its associated feedbacks. The fact that we currently lack sufficient
understanding to establish complex ecological communities with a full
complement of functioning interactions may account for disappointing and
inconsistent results when probiotics have been used to treat vulvovaginal candidiasis
and antibiotic-associated diarrheas: merely adding organisms to a complex
system—even in large amounts—can be insufficient to lead to a healthy
community structure [14, 15].
5. Integrating the Conceptualizations: Future Research on the Human Microbiota and Health
The Human Microbiome Project (HMP) is a major roadmap initiative
of the National Institutes of Health (NIH) [8]. Each NIH institute has been
exploring various ways to meet the goals of the initiative, primarily from an
organ viewpoint, in keeping with the organization of the institutes by disease
or organ system. As the HMP moves forward, it would benefit from the development
of an overall conceptual framework for structuring the research agenda,
analyzing the resulting data, and applying the results in order to improve
human health. Given the complexity of interactions among organisms in the human
microbiota and the complexities and variations of human hosts and the organisms
that inhabit those hosts, a catalog of microbes even from a range of multiple,
diverse, individuals is only a first step towards the ultimate goal of
manipulating human microbiota to prevent and treat disease. Further progress
will require understanding the drivers of change in human microbiota that lead to disease states, particularly the
underlying mechanisms and functions of microbiota, and how to establish and
maintain communities consistent with health. Understanding the mechanisms and
functions that process inputs and lead to outputs will enhance our
ability to consistently manipulate the microbiota in the form of medical
interventions and to minimize the unintended consequences of those
interventions.
The level
of complexity required to take a dynamic ecological view of human microbiota is
daunting and will require collaborations among many disciplines including molecular
biology, ecology, medicine, epidemiology, and mathematics. To fully understand
the mechanisms that drive community structure and function, microbiota must be
examined over time to determine the dynamics of its processes and over space to
determine the interconnectedness of microbiota within an individual host and
the range of microbiota among individuals. A comparison of microbiota among
individuals living in countries with poorer sanitation to those with high
levels of sanitation might be particularly interesting, in that normal,
healthy, microbiota from less developed areas may regularly include
helminthes. Moreover, these studies will
require testing large numbers of diverse individuals, as the range of what is “healthy”
or “normal” is probably very wide and may depend, in part, on the genetic
make-up of the host and the associated environment. In addition, experimental
approaches will be essential to interpret descriptive studies. Experiments in well-controlled model systems such
as bioreactors or animal models will be useful to isolate subsets of the
interacting components depicted in the dynamic ecological community model (Figure 1(d)). Such experiments will provide a critical bridge between descriptions of
highly diverse communities that change over time and space on one hand and the
logistically intractable task of experimental investigation of all possible
interaction pathways in such communities. Isolating key components of
communities for intensive study of interactions has been very successful in
understanding the ecology of macrocommunities [16–19]. Finally, mathematical models that require
specification of the hypothesized underlying systems will enable conduct of simulation
experiments to understand direct and indirect effects. The validity of
simulation experiments depends heavily on the data available to “dock” the
model. All of these approaches should lean heavily on well-developed ecological
and evolutionary theories to form hypotheses and testable, quantifiable
predictions.
Neither of the two extreme conceptualizations
of the human microbiota, the multicelled organ and the ecological community
model, are likely to be the most useful; integrated conceptualizations may be
most appropriate for different research questions or clinical problems. Regardless of our conceptualization, however,
we need to recognize that implicit assumptions yield different predictions on the
impact of microbiota function on human health and move the research agenda in
different ways. As the biomedical community moves into this rapidly burgeoning
area, funds should be set aside to explore and develop theoretical
underpinnings that draw on existing ecological and evolutionary theories and, thus, hasten efforts towards the
ultimate goal of maintaining a healthy microbiota to maintain human health.
Acknowledgments
The
authors would like to thank colleagues Daniel Clemans, John Erb-Downward, Carl
F. Marrs, and Gary Huffnagel for their contributions to discussions leading to
this manuscript and the Center for Molecular and Clinical Epidemiology of
Infectious Diseases, the Center for Study of Complex Systems, and the Rackham Graduate School at the University of Michigan
for support of workshops that stimulated discussions leading to this
manuscript. All authors claim no conflicts of interest.