Over the past few decades, abundant epidemiologic data have revealed an inverse correlation between exposure to microbes and the incidence of autoimmune and/or atopic diseases (Fig. 459-5). This type of epidemiologic correlation led to the proposal of the “hygiene hypothesis” in 1989. Initially, this hypothesis focused on the development of atopic diseases in young children, with the idea that these epidemiologic observations could “be explained if allergic diseases were prevented by infection in early childhood, transmitted by unhygienic contact with older siblings, or acquired prenatally from a mother infected by contact with her older children.”1 In fact, this notion that differences in living conditions and environmental exposures contribute to susceptibility to hay fever (summer catarrh) dates back to at least the early nineteenth century. The hygiene hypothesis has continued to evolve over the past three decades and now posits that inadequacies in microbial exposure—in combination with genetic susceptibilities—lead to a collapse of the normally highly coordinated, homeostatic immune response. At its core, the hygiene hypothesis holds that specific early-life microbial exposures are required to prevent subsequent disease and that the “Westernization” of society has led to a decrease in such exposures. This concept is now being applied beyond atopic diseases to other inflammatory and autoimmune diseases and is thought to reflect processes that occur in later life as well.
There was an inverse relationship between the incidence of select infectious diseases and the incidence of autoimmune disorders during the latter half of the twentieth century. A. Relative incidence of prototypical infectious diseases from 1950 to 2000. B. Relative incidence of select autoimmune disorders from 1950 to 2000. (From JF Bach: The effect of infections on susceptibility to autoimmune and allergic diseases. N Engl J Med 347:911, 2002. Copyright ©2002, Massachusetts Medical Society. Reprinted with permission from Massachusetts Medical Society.)
RELATIONSHIP BETWEEN THE MICROBIOTA AND SPECIFIC DISEASE STATES
The ideas inherent in the hygiene hypothesis—in sum, that microbial exposure can affect long-term health outcomes—laid the theoretical foundation for translational microbiome studies. While most of the studies described earlier sought to describe how the microbiota responds to specific and often transient influences (e.g., a course of antibiotics, dietary interventions, travel), a multitude of studies have characterized the microbiota in patients with various diseases in the hope that a better understanding of the nature of disease-specific microbial communities will provide insight into disease pathogenesis and potentially uncover novel treatment modalities. Remarkably, virtually all of these studies have demonstrated differences between the microbiotas of healthy controls and patients, irrespective of the specific disease process examined. Although it is difficult to generalize across all studies, a couple of general themes have emerged. First, disease states are typically associated with microbiotas that are less diverse than those of healthy individuals. This loss of diversity can be measured either as a decrease in the number of species (alpha diversity; often measured as the number of operational taxonomic units, which are the bioinformatic equivalent of species) or as a reduction in the microbial relatedness of the species present (beta diversity). Often, both alpha and beta diversity decrease in the setting of disease. Second, states of inflammation—regardless of site or underlying disease process—are often associated with a relative increase in the abundance of the bacterial family Enterobacteriaceae and a decrease in the abundance of Lachnospiraceae.
Dissecting Correlation and Causality
Given that most of these investigations have been designed as case–control studies, it is difficult to determine whether microbiologic findings are the cause or the effect of the disease. Even studies that examine treatment-naïve patients at the time of initial diagnosis are still confounded by this “chicken or egg” issue. Moreover, prospective, longitudinal clinical studies—still rare in the microbiome field—may simply yield correlations between the microbiome and subclinical disease rather than necessarily proving causality. Experiments in animals—specifically, studies using gnotobiotic mice (germ-free mice that have been colonized with specified microbial communities)—have been critical in this regard as they allow investigation of specific differences in microbial components while controlling for the host’s genetics, diet, and housing conditions. Moreover, human microbes can be transplanted into gnotobiotic mice to permit in-depth mechanistic studies of how these microbial communities affect disease pathogenesis. This marriage of human samples and animal experiments has facilitated the identification of causal roles played by some microbes in disease pathogenesis; these findings provide a critical proof of concept for the interplay of the microbiota with human health. However, the vast majority of microbiome studies are still at the level of correlation. The next several sections describe the clinical and animal data for many different disease processes. Given the voluminous and rapidly changing nature of this field, it is impossible to cover all of the disease associations known to date; rather, the following discussion represents a combination of the leading exemplars of microbiome data and nascent areas of significant clinical interest. In all cases, the hope is that further study of the role of the microbiota will provide novel diagnostics, new therapeutic modalities, and/or additional insight into disease pathogenesis.
Given that the intestines harbor the largest number and greatest diversity of organisms in the body, much work has focused on how the microbiota impacts gastrointestinal diseases. Even though the luminal surface area of the gastrointestinal tract is 30–40 square meters (~90% of which is contained within the small intestine) and features marked anatomic and functional differences that result in many discrete macro- and micro-ecosystems, stool is often used as a surrogate for the intestinal microbiota given the relative ease of collecting samples. A few studies that have compared the microbial profile in stool with the mucosa-adherent organisms present in biopsy samples have demonstrated that stool is, in fact, a reasonable proxy for biopsy samples; however, the relative microbial “noise” present in stool can sometimes overwhelm the “signal,” making biopsy samples more informative for some scientific questions. The key issue is to ensure that the biopsy samples evaluated represent relatively similar intestinal regions, as there are significant differences between the organisms present in the crypt and the tip of the villus and between microbes found in the ascending versus the descending colon.
Obesity is a worsening epidemic throughout the world, and multiple studies have linked the composition of the intestinal microbiota to the development of obesity in animal models and in humans. Indeed, many of the initial translational microbiome studies performed in mice at the beginning of the twenty-first century focused on obesity. These early studies suggested that the ratio of the relative abundance of Bacteroidetes to Firmicutes was lower in obese mice than in control animals. Moreover, a causal relationship between the microbiota and obesity was established by the finding that gnotobiotic mice colonized with the microbiota from obese individuals had more rapid and more extensive weight gain than gnotobiotic mice colonized with the microbiota from lean individuals. Biologically, it is posited on the basis of metagenomic surveys that the obesity-associated microbiome has an increased capacity to harvest energy from the diet. Notably, the relationship between the Bacteroidetes/Firmicutes ratio and obesity did not hold in initial human studies; however, the finding that this ratio increased in obese patients who lost weight while on a fat- or carbohydrate-restricted diet suggested some generalizability between mice and humans. Beyond this ratio of major bacterial phyla, obesity was linked to a microbiome with a lower alpha diversity. Over the past ~15 years, numerous human studies examining the relationship between the microbiome and obesity have been completed, all with mixed results. A recent meta-analysis of 10 studies including nearly 3000 individuals revealed an apparent lack of relationship between the Bacteroidetes/Firmicutes ratio and obesity, though there is ~2% lower diversity associated with obesity that is statistically significant but of unclear biological significance. This finding highlights a problem common to microbiome studies: i.e., there is no sense as to what magnitude of change is biologically meaningful. Ultimately, although murine studies have indicated a causal link between the microbiota and obesity, the human data are less convincing, and their significance may be limited by the studies’ having primarily examined only high-level taxonomic information rather than also assessing transcriptional or metabolic differences.
The rise in obesity has elicited a plethora of ideas about the type of diet that might be most successful in leading to sustained weight loss. It has become clear that the same dietary ingredient can have highly diverse effects on blood glucose measurements in different people and that this effect is mediated largely by the microbiome. These observations suggest that the “optimal” diet needs to be individualized in the context of the person’s microbiome, which itself may continue to change over the course of the diet. An intriguing parallel question is whether the microbiota may also influence dietary preferences; such an influence would suggest important feedback loops between the microbiome and diet.
Representing the other end of the metabolic spectrum from obesity, malnutrition is also linked to an altered microbiome. Analysis of Malawian twin pairs (≤3 years of age) who were discordant for kwashiorkor—a severe form of malnutrition—revealed that kwashiorkor is associated with a microbiologically “immature” fecal microbiota that resembles that of a chronologically younger child. Transplantation of the fecal microbiota from these discordant twins into gnotobiotic mice that were fed a diet similar in composition to a typical Malawian diet established that the kwashiorkor-associated microbiome is causally related to poor weight gain. Subsequent studies demonstrated these same general trends in malnourished Bangladeshi children. Investigators were able to identify five bacterial species (Faecalibacterium prausnitzii, Ruminococcus gnavus, Clostridium nexile, Clostridium symbiosum, and Dorea formicigenerans) that—when administered together as a “cocktail” to mice colonized with a kwashiorkor-associated microbiome—was able to prevent growth impairments. These results demonstrate that rationally designed modulation of the murine microbiota can lead to improved health outcomes. The clinical significance of these findings for humans remains to be clarified.
INFLAMMATORY BOWEL DISEASE
Ulcerative colitis and Crohn’s disease, the two predominant forms of inflammatory bowel disease (IBD), are chronic gastrointestinal inflammatory conditions that differ in their locations and patterns of inflammation (Chap. 319). The following observations have led to the suggestion that IBD is the result of an immune response to a dysbiotic microbiota in a genetically susceptible individual: genes account for only ~20% of susceptibility to IBD (and many of the relevant genes are related to host–microbe interactions), antibiotic treatment reduces the clinical severity of disease, and relapses of Crohn’s disease are prevented by diversion of the fecal stream. While the microbiota clearly is not the only driver of disease, it is considered to be an important element. Accordingly, numerous animal and clinical studies have been designed to tease out the nature of the relationship between the microbiota and IBD.
Most of these studies have focused on comparing the microbiome’s composition in IBD patients with that in healthy controls, concentrating on microbial diversity and specific bacterial taxa that are associated with health or disease. Unfortunately, few, if any, results have been universally obtained, probably because of differences in study design, inclusion criteria, and methodology (e.g., the use of stool, rectal swabs, or biopsy samples; the choice of sequencing primers; the analysis pipeline). Even with these differences among studies, patients with IBD have been shown typically to have reduced alpha and beta diversity in their fecal microbiotas. Moreover, Clostridium clusters IV and XIVa, which are polyphyletic and encompass several different bacterial families, are generally reduced in patients with IBD. F. prausnitzii is a notable example from Clostridium cluster IV that is often underrepresented in the stool of patients who have Crohn’s disease, with more mixed results in biopsy samples. The bacterial family Lachnospiraceae, which is largely contained in Clostridium cluster XIVa, and other butyrate-producing organisms are also reduced in the stool of patients with IBD. Some of these species produce butyrate by using acetate generated by other members of the microbiome, and some of these acetate-producing species are similarly reduced (e.g., Ruminococcus albus). These complex interactions and dependencies among bacterial species pose unique challenges to definitive ascertainment of the cause–effect relationships between microbes and disease. Even before researchers were able to assess the entire microbiome at once, they often noted that patients with Crohn’s disease had a higher representation of adherent invasive E. coli in the ileal mucosa, an observation consistent with the increased abundance of Enterobacteriaceae seen in more recent microbiome studies. Beyond bacteria, burgeoning evidence supports a role for Caudovirales bacteriophages in IBD pathogenesis, though these findings may merely reflect the underlying dysbiosis related to the loss of bacterial diversity in IBD. Moreover, some data suggest that IBD is also associated with fungal dysbiosis; several studies have demonstrated an increased ratio of Basidiomycota to Ascomycota. It is still unclear whether any of these microbial associations reflect the cause of IBD or merely serve as biomarkers of disease.
Studies of antibiotic-treated mice and gnotobiotic mice colonized with IBD-associated microbiotas have been useful in confirming that the microbiota affects colitis severity. Several bacterial species have been identified as either promoting colitis in mice (e.g., Klebsiella pneumoniae, Prevotella copri) or protecting against it (e.g., Bacteroides fragilis, Clostridium species); however, these organisms do not always correlate with the taxa identified as differentially abundant across multiple clinical studies. In contrast, IgA-coated commensal organisms isolated from patients with IBD promote more severe colitis in mice than either IgA-uncoated bacteria from patients with IBD or IgA-coated bacteria from healthy controls. These data suggest that functional categorization of the microbiota based on immune recognition (e.g., IgA coating) may be a useful approach for identifying pathogenic organisms.
Inflammation helps drive the pathogenesis of atherosclerosis, and it has long been postulated that microbes are involved in the atherosclerotic process. Early work demonstrated that patients with cardiovascular disease have higher titers of antibody to Chlamydia pneumoniae than control patients, that C. pneumoniae is present within atherosclerotic lesions, and that C. pneumoniae can both initiate and exacerbate atherosclerotic lesions in animal models. This type of analysis has been extended to other bacteria, such as Porphyromonas gingivalis, with the idea that multiple different bacteria may play some role in the pathogenesis of atherosclerosis.
More recent studies have demonstrated clinical correlations between serum levels of trimethylamine N-oxide (TMAO) and atherosclerotic heart disease. Given that red meat, eggs, and dairy products are important sources of carnitine and choline (both precursors of TMAO), it is not surprising that levels of TMAO are higher in omnivores than in vegans. Animal studies have confirmed that transfer of the gut microbiota from atherosclerosis-susceptible strains of mice to atherosclerosis-resistant animals leads to increased serum levels of TMAO and a dietary choline-dependent increase in atherosclerotic plaques; this observation confirms the role of the gut microbiota in the generation of TMAO and atherosclerosis. Moreover, treatment of atherosclerosis-susceptible strains of mice with a structural analogue of choline that inhibits the first enzymatic step in TMAO formation leads to decreased circulating TMAO levels and, more importantly, restrains macrophage foam-cell formation and atherosclerotic lesion development. In a study of more than 4000 patients, plasma TMAO levels were also predictive of incident thrombosis risk (myocardial infarction, stroke). Gnotobiotic animals were used to demonstrate that this risk was dependent on the microbiota; although eight bacterial taxa were identified as being associated with both plasma TMAO levels and thrombotic risk, organisms with choline-utilization genes that represent the first step of TMAO production were not more abundant in animals at greater risk for thrombosis. This discrepancy highlights the complexity of the microbiota and suggests that other aspects of the overall dynamics of the microbial community may be in play.
Recent studies exploring the link between the microbiota and cancer have demonstrated that specific members of the microbiota can affect treatment efficacy in both a positive and a negative manner. For example, therapy with antibody to programmed cell death ligand 1 (anti-PD-L1) has proven highly effective for a number of different cancers (Chap. 69); however, a significant proportion of patients do not respond even when their tumors have high PD-L1 expression levels, a prerequisite for this type of checkpoint blockade inhibition. Using a murine melanoma model, investigators showed that variations in the microbiota resulted in differences in melanoma growth, an impact that was accentuated by anti-PD-L1 therapy. Ultimately, Bifidobacterium species were bioinformatically associated with improved anti-tumor responses, and administration of a “cocktail” of Bifidobacterium species (B. bifidum, B. longum, B. lactis, and B. breve) to melanoma-susceptible mice resulted in improved tumor-specific immunity and responses to anti-PD-L1 therapy. In a separate set of studies involving both patient data and animal experiments, the efficacy of therapy with antibody to cytotoxic T lymphocyte–associated antigen 4 (anti-CTLA-4) was associated with T-cell responses specific for either Bacteroides theta-iotaomicron or B. fragilis. In particular, administration of B. fragilis to germ-free or antibiotic-treated mice restored the normally absent anti-cancer response to anti-CTLA-4 therapy. While both of these examples demonstrate potentiation of anti-cancer therapies by the microbiota, other therapies can be antagonized. Some cancers, such as pancreatic ductal adenocarcinoma, contain intratumor bacteria, particularly Gammaproteobacteria, that can metabolize the chemotherapeutic agent gemcitabine and thereby contribute to the drug resistance of these tumors. Overall, these examples highlight the microbiota’s critical impact—both direct and indirect—on the efficacy of drugs. Many other notable examples have been described (e.g., involving cyclophosphamide, digoxin, levodopa, and sulfasalazine), and many more likely remain to be discovered.
The application of microbiome science to hematopoietic stem cell transplantation (HSCT) is an area of expanding interest, particularly given the significant morbidity and mortality related to graft-versus-host disease (GVHD). In light of studies in the 1970s showing that germ-free mice developed less frequent and less severe gut GVHD than wild-type mice, clinicians began to use antibiotics to decontaminate the gut of patients undergoing HSCT. This decontamination approach yielded mixed results, probably because of differences in the antibiotic regimens used. The natural history of patients undergoing allogeneic HSCT includes a substantial loss of diversity in the fecal microbiota, with lower levels of bacterial diversity associated with increased mortality. Moreover, a retrospective analysis of ~850 patients undergoing allogeneic HSCT revealed that receipt of imipenem-cilastatin or piperacillin-tazobactam for neutropenic fever was associated with increased GVHD-related mortality at 5 years; this observation suggested that specific bacteria may help protect against GVHD-related mortality. More detailed analyses revealed an association between the abundance of Blautia species and protection against GVHD and mortality, though this correlation is still being examined with regard to its causal relationship. Despite significant interest in examining these microbial relationships with HSCT, little has yet been studied in the context of solid organ transplantation, which likely represents the next frontier of transplantation-related microbiome investigation.
The dramatic rise in the incidence of many autoimmune diseases over the past few decades has been far more rapid than can be explained simply by genetic factors (Fig. 459-5). It is increasingly thought that environmental triggers, including the microbiome, are partially responsible for the development of these autoimmune diseases.
Type 1 diabetes (T1D) is an autoimmune disorder characterized by T cell–mediated destruction of insulin-producing pancreatic islets (Chap. 396). There is a clear genetic predisposition for the disease: ~70% of patients with T1D have human leukocyte antigen (HLA) risk alleles. However, only 3–7% of children with these risk alleles actually develop disease, an observation that suggests a role for other environmental factors. Studying a prospective, densely sampled, longitudinal cohort of at-risk, HLA-matched children from Finland and Estonia, investigators detailed changes in the microbiota prior to development of disease. Although only 4 of the 33 children studied developed T1D within the time frame of the study, a marked decrease of ~25% in alpha diversity occurred after seroconversion but before disease diagnosis. The low number of cases in this study unfortunately precluded identification of any specific disease-associated taxa. A follow-up study compared the microbiomes of a larger cohort of these high-risk northern European children with those of low-risk Russian children who lived in geographic proximity. Bacteroides species were more abundant in the high-risk group than in the low-risk group, particularly at early ages. This difference was postulated to be associated with an altered structure of the bacterial lipopolysaccharide to which children were exposed at a young age. It was further suggested that Bacteroides-derived lipopolysaccharide was not able to provide the immunogenic stimulus necessary to prevent T1D. These two studies offer attractive—though logistically complicated—options for future clinical investigations aimed at exploring the role of the microbiome. The first approach—longitudinally following individuals who are at high risk for a given disease—may provide insight into host–microbe relationships by mapping temporal changes in the microbiome with disease onset. An important caveat with this type of study, though, is that the associations identified may reflect preclinical disease rather than specifically indicating causality for any observed changes. The second approach illustrates how careful selection of study participants may offer an opportunity to uncover more meaningful associations that can subsequently be experimentally verified.
Similar to many other autoimmune diseases, rheumatoid arthritis (RA) is a multifactorial disease that comes to clinical attention after an environmental factor triggers symptoms in an individual with pre-existing autoantibodies. Multiple lines of evidence support the notion that RA pathogenesis is reliant on the microbiota, including the findings that germ-free mice do not develop symptoms in several RA models and that antibiotic treatment of mice mitigates against RA development. Several taxa (e.g., Bacteroides species, Lactobacillus bifidus, and segmented filamentous bacteria) have been implicated in promoting RA in murine models, and analysis of the fecal microbiota of patients with newly diagnosed RA have indicated that P. copri is a biomarker of disease. That this association with P. copri does not exist for chronic, treated RA or for psoriatic arthritis suggests some specificity for new-onset RA. A major limitation of this approach is that the identified association is shown to be a biomarker of disease (and, in this case, potentially of response to treatment) but no added insight is gained into a possible causal relationship between P. copri and RA. In fact, many of the patients with new-onset RA had no Prevotella detected, and several of the healthy controls had significant levels of Prevotella. The lack of a strict concordance between the presence (or absence) of a specific taxon and a given disease state argues against a possible causal role.
Epidemiologic studies of twin pairs and at-risk individuals moving between high- and low-risk geographic areas indicate that genetics plays a minor component in multiple sclerosis (MS) susceptibility relative to environmental factors. For example, in monozygotic twin pairs in which one sibling has MS, the other sibling also develops MS in only ~30% of cases. Although MS is a disease of the central nervous system (CNS), there is growing evidence of a link between MS and the microbiota, specifically that of the gut. Germ-free animals and antibiotic-treated animals display reduced disease incidence and severity in an MS model. Similarly, some clinical studies suggest improved disease outcomes in patients with MS who have been treated with minocycline, while patients treated with long-term penicillin appear to have an increased disease risk. Although several studies have compared the fecal microbiotas of healthy controls to those of patients with MS, these studies have all been relatively small and have yielded few results (if any) that are common throughout. Although work relating the microbiome to MS is ongoing, it has opened the door to exploring this link with other neurologic diseases. Already, there are animal data demonstrating links between the microbiota and both Parkinson’s disease and autism, and there are clinical data assessing fecal microbiomes in relation to a variety of neurologic conditions. It is not quite clear how the gut microbiota is communicating with the CNS—i.e., whether communication takes place via bacterial metabolites that travel in the bloodstream and cross the blood–brain barrier, via migration of whole organisms into the CNS, or via feedback through the vagus nerve. Although our understanding of this brain–gut axis is still in its infancy, research in this area has elicited tremendous excitement as a tractable approach to potential treatments for these challenging diseases.
The incidence and prevalence of allergic diseases continue to steadily increase, as do more severe clinical presentations. Life-threatening food allergies are now such a public health issue that nut-free classrooms are the norm in many cities. The development of allergic diseases often follows a stereotyped progression that begins with atopic dermatitis (AD) and continues, in order, with food allergy, asthma, and allergic rhinitis. The microbiome has been linked to all of these conditions and has the potential to modulate effects anywhere along this spectrum.
The skin is the largest organ in the body, and its different anatomic sites (e.g., antecubital fossa, volar forearm, alar crease) represent distinct ecologic niches and harbor unique microbial communities. Moreover, given that the skin serves as a critical interface between the body and the external environment (e.g., microbes), it must be able to respond to unwanted microbes with an adequate immune response. AD is an inflammatory skin disorder involving immune dysfunction and a dysbiotic skin microbiota that is typically marked by greater abundances of Staphylococcus aureus and a lesser degree of bacterial diversity. Effective treatment of AD does not require complete elimination of S. aureus but is associated with restoration of the normal level of diversity. It is likely that this increase in bacterial diversity re-establishes normal immune homeostasis in the skin; specific members of the skin microbiota have been shown to induce protective skin-restricted immune responses. Coagulase-negative staphylococci (CoNS; primarily S. epidermidis and S. hominis) obtained from lesional and nonlesional skin of patients with AD were functionally screened and compared to CoNS from healthy controls; AD-lesional CoNS were much less often able to produce antimicrobial peptides (lantibiotics) directed against S. aureus. To demonstrate that these lantibiotic-producing CoNS were biologically relevant, they were incorporated into a lotion and applied to the arms of patients with AD. Surprisingly, a single application of the probiotic-laced lotion led to a decrease in the abundance of S. aureus recovered; no such decrease was observed when lantibiotic-negative strains were used. The authors of this study did not specifically comment on the clinical improvement of the AD lesions. Nevertheless, this is one of a limited number of studies that is beginning to extend microbiome-related findings into clinical trials.
Asthma is characterized by the clinical triad of airflow obstruction, bronchial hyperresponsiveness, and inflammation in the lower respiratory tract. Although the long-standing dogma was that the lungs are sterile, there is now convincing evidence for a constant ebb and flow of bacteria within the lower airways. In healthy states, the mucociliary escalator continually eliminates these bacteria soon after they land in the airways; in disease states (e.g., cystic fibrosis, chronic obstructive pulmonary disease), these bacteria establish long-term colonization of the airways and influence disease pathogenesis. In asthma specifically, both fecal and airway microbes have been linked to clinical outcomes.
Early studies of the microbiome’s influence on asthma used culture-based methods to assess the hypopharyngeal microbiota of asymptomatic 1-month-old infants. Intriguingly, in one study, early-life colonization with Streptococcus pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, or a combination of these organisms—but not S. aureus—was significantly associated with persistent wheeze and asthma at 5 years of age. Eosinophilia and total IgE levels at 4 years of age were also increased in children who were neonatally colonized with these organisms. Although this study examined a fairly focused set of bacteria, it laid the experimental groundwork indicating that early-life microbial exposures influence subsequent development of asthma. A later longitudinal investigation of the fecal microbiota in a general-population birth cohort of more than 300 children demonstrated that lower abundances of the genera Lachnospira, Veillonella, Faecalibacterium, and Rothia at 3 months of age were associated with an increased risk for development of asthma. The fact that these bacterial changes were no longer apparent when the children were 1 year of age is consistent with the notion that microbial exposures early in life are important to disease pathogenesis later in life. Transplantation of stool samples from 3-month-old children at risk for asthma into gnotobiotic mice resulted in significant airway inflammation in a murine model of asthma; pre- and postnatal exposure of mice to a four-species cocktail (F. prausnitzii, Veillonella parvula, Rothia mucilaginosa, and Lachnospira multipara) inhibited airway inflammation, with a marked reduction in neutrophil numbers in bronchoalveolar lavage fluid. These data suggest that early-life modulation of the microbiome may be an effective strategy to help prevent asthma, though the specific logistics (e.g., strains, dose, timing of exposure, patient selection) remain to be clarified.
The increased susceptibility of antibiotic-treated mice to infection with a wide range of enteric pathogens was initially observed in the 1950s and led soon thereafter to the concept of colonization resistance, which holds that the normal intestinal microbiota plays a critical role in preventing colonization—and therefore disease production—by invading pathogens. Seminal work in the 1970s demonstrated that this protection is largely reliant on clostridial organisms, and the subsequent half-century has been spent trying to identify the specific microbes involved. Although much of the work relating the microbiota to infection has focused on enteric pathogens, the intestinal microbiota has also been clearly linked to bacterial pneumonia in mouse models, and changes in the microbial composition of the gut have been causally related to changes in the severity of disease. Although this gut–lung axis clearly exists in animals, its relevance in humans is still unclear. Several groups are beginning to study the human lung microbiome in the context of pneumonia and tuberculosis. Moreover, the relationships between the microbiota and both systemic infections (e.g., HIV infection, sepsis) and the response to vaccination are starting to be explored.
Clostridium difficile infection (CDI) represents a growing worldwide epidemic and is the leading cause of antibiotic-associated diarrhea (Chap. 129). Roughly 15–30% of patients who are successfully treated for CDI end up with recurrent disease. The strong association between antibiotic exposure and CDI initially raised the idea that the microbiota is inextricably linked to acquisition of disease, presumably because of the loss of colonization resistance. Consistent with the epidemiologic data, characterization of the fecal microbiota of patients with CDI revealed that it is a markedly less diverse, dysbiotic community. Fecal microbiota transplantation (FMT)—the “transplantation” of stool from a healthy individual into patients with disease—was successfully used in the 1950s to treat four patients with severe CDI and has recently been demonstrated in numerous studies to be an effective therapy for recurrent CDI, with clinical cure in 85–90% of patients (as detailed below). Thus, FMT for recurrent CDI has become the “poster child” for the idea that microbiome-based therapies may transform the management of many diseases previously considered to be refractory to medical therapy. Although FMT is agnostic as to the underlying mechanism of protection, work is ongoing to identify specific microbes and host pathways that can protect against CDI. Studying mice with differential susceptibilities to CDI due to antibiotic-induced changes in their microbiota, investigators identified a cocktail of four bacteria (Clostridium scindens, Barnesiella intestihominis, Pseudoflavonifractor capillosus, and Blautia hansenii) that conferred protection against CDI in a mouse model. Intriguingly, treatment of mice with just C. scindens offered significant, though not complete, protection in a bile acid–dependent manner. Clinical data from patients who underwent HSCT also associated C. scindens with protection from CDI, an observation that suggests the possibility of translating these findings from mice to humans. This study provides another example of the identification of relevant bacterial factors through examination of microbial differences in populations that differ in disease risk.
Microbiome-related changes associated with Vibrio cholerae infection include a striking loss of diversity (largely due to V. cholerae’s becoming the dominant member of the microbiota) and an altered composition that rapidly follows the onset of disease. These changes, which occur in a reproducible and stereotypical manner, are reversible with treatment of the disease. This recovery phase involves a microbial succession that is similar to the assembly and maturation of the microbiota of healthy infants. In addition to V. cholerae, streptococcal and fusobacterial species bloom during the early phases of diarrhea, and the relative abundances of Bacteroides, Prevotella, Ruminococcus/Blautia, and Faecalibacterium species increase during the resolution phase and mark the return to a healthy adult microbiota. Analysis of these microbial changes occurring in patients with cholera and in healthy children led to the selection of 14 bacteria that were transplanted into gnotobiotic mice, which were then challenged with V. cholerae. Bioinformatic analysis of specific taxa changing during cholera determined that Ruminococcus obeum restrained V. cholerae growth. Subsequently, this relationship was experimentally confirmed, and the R. obeum quorum-sensing molecule AI-2 (autoinducer 2) was found to be responsible for restricting V. cholerae colonization via an unclear mechanism. These studies highlight the potential for use of microbiome-based therapies to prevent and/or treat infectious diseases. Moreover, they suggest that temporal analysis of longitudinal microbiome data may be an effective strategy for identifying microbes with causal relationships to disease.
The augmentation of HIV pathogenesis by some viral, bacterial, and parasitic co-infections suggests that a patient’s underlying microbial environment can influence the severity of HIV disease. Moreover, it has been hypothesized that the intestinal immune system plays a significant role in regulating HIV-induced immune activation; this seems particularly likely since the intestines are an early site for viral replication and exhibit immune defects before peripheral CD4+ T cell counts decrease. Several studies have examined the intestinal microbiotas of HIV-infected individuals. Initial studies performed in nonhuman primates infected with simian immunodeficiency virus found no alteration in the bacterial components of the fecal microbiota; however, there were profound changes in the enteric virome. In contrast, many recent studies exploring this issue in patients have identified substantial differences in the HIV-associated fecal microbiota that correlate with systemic markers of inflammation. Curiously, these microbial changes do not necessarily normalize with antiretroviral therapy; this finding suggests that the microbiota may have some “memory” of the previously high HIV loads and/or that HIV infection helps reset the “normal” microbiota. This memory-like capacity of the microbiota has been demonstrated in animal models in the context of other infections and in response to dieting.
Given that the majority of new HIV transmission events follow heterosexual intercourse, there has been significant interest in examining the relationship between the vaginal microbiota and HIV acquisition. A longitudinal study of South African adolescent girls who underwent high-frequency testing for incident HIV infection facilitated the identification of bacteria that were associated with reduced risk of HIV acquisition (Lactobacillus species other than L. iners) or with enhanced risk (Prevotella melaninogenica, Prevotella bivia, Veillonella montpellierensis, Mycoplasma, and Sneathia sanguinegens). In mice inoculated intravaginally with Lactobacillus crispatus or P. bivia, the latter organism induced a greater number of activated CD4+ T cells in the female genital tract, a result suggesting that the increased risk of HIV acquisition associated with P. bivia may be secondary to the increased presence of target cells. In a separate study, the composition of the vaginal microbiota was shown to modulate the antiviral efficacy of a tenofovir gel microbicide. Although tenofovir reduced HIV acquisition by 61% in women who had a Lactobacillus-dominant vaginal microbiota, it reduced HIV acquisition by only 18% in women whose vaginal microbiota comprised primarily Gardnerella vaginalis and other anaerobes. This difference in efficacy was due to the ability of G. vaginalis to metabolize tenofovir faster than the target cells can take up the drug and convert it into its active form, tenofovir diphosphate. These findings illustrate how microbial ecology can be an important consideration in choosing effective treatment regimens.
Second only to the provision of clean water, vaccination has been the most effective public health intervention in the prevention of serious infectious diseases. Its effects are mediated by antigen-specific antibodies and, in some cases, effector T-cell responses. Although vaccines are clearly effective on a population scale, the magnitude of the immune response to vaccines can vary among individuals by tenfold to a hundredfold. Although many factors (e.g., genetics, maternal antibody levels, prior antigen exposures) can affect vaccine immunogenicity, the microbiota is now recognized as another important factor. Analysis of the fecal microbiotas of ~50 Bangladeshi children identified specific taxa that exhibited positive associations (e.g., Actinomyces, Rothia, and Bifidobacterium species) and negative associations (e.g., Acinetobacter, Prevotella, and staphylococcal species) with responses to vaccines against polio, tuberculosis (bacille Calmette-Guérin), tetanus, and hepatitis B. A study of infants from Ghana revealed an inverse relationship between the fecal abundance of Bacteroidetes and a response to the rotavirus vaccine. Moreover, the nasal microbiota has been implicated as a factor that contributes to the IgA response to live, attenuated influenza vaccines. These correlations based on clinical data have been partially confirmed in animal studies. The best example is the demonstration that the responses to non-adjuvanted viral subunit vaccines (inactivated influenza and polio vaccines) are reliant on the microbiota, whereas the responses to live or adjuvanted vaccines (live attenuated yellow fever, Tdap/alum, an HIV envelope protein/alum vaccine) are not. An interesting note is that the antibody response to inactivated influenza vaccine is dependent on recognition of the microbiota by Toll-like receptor 5, presumably via flagellin-expressing microbes. These data suggest that the microbiota may serve as an adjuvant for certain vaccine types. Confirmation of these findings in clinical settings may suggest ways to improve vaccine efficacy in the future.