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InternalMed_Harrison. vary dramatically in their representation among different samples, with different characteristic bacterial phyla in the oral versus the fecal microbiota; e.g., members of the Actinobacteria and Fusobacteria are far more common in the mouth than in the gut, while members of Bacteroidetes are far more common in fecal samples. In contrast, metabolic pathways are far more consistently represented in different samples, even when the species that contribute to these pathways are completely different. These results suggest a high degree of functional redundancy in microbial ecosystems—similar to that observed in macroecosystems, in which many fundamentally different lineages of organisms can play the same ecologic roles (e.g., pollinator or top predator). (Adapted from Human Microbiome Project Consortium: Nature 486:207, 2012; and CA Lozupone et al: Nature 489:220, 2012.) understanding of our microbiota. Few high-resolution time series of way for defining stability at the strain level than


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InternalMed_Harrison. Consortium: Nature 486:207, 2012; and CA Lozupone et al: Nature 489:220, 2012.) understanding of our microbiota. Few high-resolution time series of way for defining stability at the strain level than was available in the individual healthy adults have been published to date, but one available past. Application of these methods to the guts of healthy individualsdaily time series suggests that individuals tend to resemble themselves sampled over time has disclosed that a healthy adult gut harbors a permicrobially day to day over a span of 6–15 months, retaining their sistent collection of ~100 bacterial species and several hundred strains.separate identities during cohabitation. The development of low-error The stability of the bacterial components follows a power law: bacterial amplicon sequencing methods has provided a much more reliable strains acquired early in life can persist in the gut for decades, although their proportional representation changes as a function of numerous


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InternalMed_Harrison. sequencing methods has provided a much more reliable strains acquired early in life can persist in the gut for decades, although their proportional representation changes as a function of numerous factors, including diet. Whole-genome sequencing of culturable components of the microbiota of study participants has confirmed that strains are retained in individuals for prolonged periods and are shared among family members.


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InternalMed_Harrison. Resilience The ability of a microbiota or microbiome to rebound from a short-term perturbation, such as antibiotic administration or an infection, is defined as its resilience. This capacity can be visualized as a ball rolling over a landscape of local minima; essentially, the community moves into a new state and, to recover, must move through another, unstable state. In some cases, recovery will lead to the original stable state; in others, it will lead to a new stable state, which may be either healthy or unhealthy. Changes in, for example, diet or host physiologic status may introduce alterations into the landscape itself, making it easier to move from the initial state to any one of a number of other states, potentially with different health consequences. Microbial communities in our body habitats differ widely in resilience. For example, hand washing leads to profound changes in the microbial community, greatly increasing diversity (presumably because of the preferential removal


InternalMed_Harrison

InternalMed_Harrison. body habitats differ widely in resilience. For example, hand washing leads to profound changes in the microbial community, greatly increasing diversity (presumably because of the preferential removal of high-abundance, dominant phylotypes such as Propionibacterium). Within 6 h, the hand microbiota rebounds to resemble the original hand communities. The effects of repeated hand washing still need to be defined; for example, the surface microbiota on the skin (as measured by scrape biopsies) consists of ~50,000 microbial cells/cm2, whereas the subsurface microbiota (as measured by punch biopsies) consists of ~1,000,000 microbial cells/cm2.


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InternalMed_Harrison. In a study of three healthy adult volunteers given a short course of ciprofloxacin (500 mg by mouth twice a day for 5 days—a regimen commonly used against uncomplicated urinary tract infections), overall gut-community configuration came to resemble baseline within 6 months after treatment cessation, although some taxa failed to recover. However, the effects of the antibiotic perturbation were highly individualized. Administration of a second course of treatment months later led to altered-community states, relative to baseline, in all three volunteers; again, the extent of the alteration differed with the individual. Crucially, as shown in this and other studies, a given bacterial taxon can respond differently to the same antibiotic in different individuals; this observation suggests that the rest of the microbial community plays an important role in determining the effects of antibiotics on a per-individual basis.


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InternalMed_Harrison. In any body habitat, the microbial-community state after disturbance may be degraded. However, this degraded state may itself be resilient, and it may therefore be difficult to restore a more functional state. For example, Clostridium difficile infection can persist for years. The development and resilience of a degraded state may be driven by positive feedback loops, such as reactive oxygen species cascades involving host macrophages that promote the further growth of proinflammatory Proteobacteria, as well as negative-feedback loops such as depletion of the butyrate needed for promotion of a healthy gut epithelial barrier and further establishment of beneficial members of the microbiota. Consequently, microbiota-based therapies may require either (1) the elimination of a feedback loop that prevents establishment of a new community or (2) identification of a direction for change and a stimulus of sufficient magnitude (e.g., invasion and establishment of microbes from a fecal


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InternalMed_Harrison. loop that prevents establishment of a new community or (2) identification of a direction for change and a stimulus of sufficient magnitude (e.g., invasion and establishment of microbes from a fecal transplant or from a defined consortium of cultured, sequenced members of the human gut microbiota; see below) to overcome the resilience mechanisms inherent in the degraded state. A critical unresolved question that especially affects infants, whose microbiota is changing rapidly, is whether intervention during periods of rapid change or during periods of relative stability is generally more effective.


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InternalMed_Harrison. ESTABLISHING CAUSAL RELATIONSHIPS BETWEEN THE GUT MICROBIOTA AND NORMAL PHYSIOLOGIC, METABOLIC, AND IMMUNOLOGIC PHENOTYPES AS WELL AS DISEASE STATES Gnotobiotic animals are raised in germ-free environments—with no exposure to microbes—and then colonized at specific stages of life with specified microbial communities. Gnotobiotic mice provide an excellent system for controlling host genotype, microbial community composition, diet, and housing conditions. Microbial communities harvested from donor mice with defined genotypes and phenotypes 86e-7 can be used to determine how the donors’ microbial communities affect the properties of formerly germ-free recipients. The recipients may also affect the transplanted microbiota and its microbiome. Thus gnotobiotic mice afford investigators an opportunity to marry comparative studies of donor communities to functional assays of community properties and to determine how (and for how long) these functions influence host biology.


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InternalMed_Harrison. The Cardiovascular System The gut microbiota affects the elaborate microvasculature underlying the small-intestinal epithelium: capillary network density is markedly reduced in adult germ-free animals but can be restored to normal levels within 2 weeks after gut microbiota transplantation. Mechanistic studies have shown that the microbiota promotes vascular remodeling in the gut through effects on a novel extravascular tissue factor–protease-activated receptor (PAR1) signaling pathway. Heart weight measured echocardiographically or as wet mass and normalized to tibial length or lean body weight is significantly reduced in germ-free mice; this difference is eliminated within 2 weeks after colonization with a gut microbiota. During fasting, a gut microbiota–dependent increase in hepatic ketogenesis (regulated by peroxisome proliferator–activated receptor α) occurs, and myocardial metabolism is directed to ketone body utilization. Analyses of isolated, perfused working hearts from


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InternalMed_Harrison. ketogenesis (regulated by peroxisome proliferator–activated receptor α) occurs, and myocardial metabolism is directed to ketone body utilization. Analyses of isolated, perfused working hearts from germ-free and colonized animals, together with in vivo assessments, have shown that myocardial performance in germ-free mice is maintained by increasing glucose utilization. However, heart weight is significantly reduced in both fasted and fed mice; this heart-mass phenotype is completely reversed in germ-free mice fed a ketogenic diet. These findings illustrate how the gut microbiota benefits the host during periods of nutrient deprivation and represent one link between gut microbes and cardiovascular metabolism and health.


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InternalMed_Harrison. Conventionally raised apoE-deficient mice develop a less severe form of atherosclerosis than their germ-free counterparts when fed a high-fiber diet. This protective effect of the microbiota is obviated when animals are fed a diet low in fiber and high in simple sugars and fat. A number of the beneficial effects attributed to diets with high proportional representation of whole grains, fruits, and vegetables are thought to be mediated by end products of microbial metabolism of dietary compounds, including short-chain fatty acids and metabolites derived from flavonoids. Conversely, microbes can convert otherwise harmless dietary compounds into metabolites that increase risk for cardiovascular disease. Studies of mice and human volunteers have revealed that gut microbiota metabolism of dietary L-carnitine, which is present in large amounts in red meat, yields trimethylamineN-oxide, which can accelerate atherosclerosis in mice by suppressing reverse cholesterol transport.


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InternalMed_Harrison. Yet another facet of microbial influence on cardiovascular physiology was revealed in a study of mice deficient in Olfr78 (a G protein– coupled receptor expressed in the juxtaglomerular apparatus, where it regulates renin secretion in response to short-chain fatty acids) or Gpr41 (another short-chain fatty acid receptor that, together with Olfr78, is expressed in the smooth muscle cells present in small resistance vessels). This study demonstrated that the microbiota can modulate host blood pressure via short-chain fatty acids produced by microbial fermentation.


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InternalMed_Harrison. Bone Adult germ-free mice have greater bone mass than their conventionally raised counterparts. This increase in bone mass is associated with reduced numbers of osteoclasts per unit bone surface area, reduced numbers of CD11b+/GR1 osteoclast precursors in bone marrow, decreased numbers of CD4+ T cells, and reduced levels of expression of the osteolytic cytokine tumor necrosis factor α. Colonization with a normal gut microbiota resolves these observed differences between germ-free and conventionally raised animals. Brain Adult germ-free and conventionally raised mice differ significantly in levels of 38 out of 196 identified cerebral metabolites, 10 of which have known roles in brain function; included in the latter group are N-acetylaspartic acid (a marker of neuronal health and attenuation),


InternalMed_Harrison

InternalMed_Harrison. Chapter 86e The Human Microbiome pipecolic acid (a presynaptic modulator of γ-aminobutyric acid levels), and serine (an obligatory co-agonist at the glycine site of the N-methyl-d-aspartate receptor). Propionate, a short-chain fatty acid product of gut microbial-community metabolism of dietary fiber, affects expression of genes involved in intestinal gluconeogenesis via a gut–brain neural circuit involving free fatty-acid receptor 3; this effect provides a mechanistic explanation for the documented beneficial impact of dietary fiber in enhancing insulin sensitivity and reducing body mass and adiposity.


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InternalMed_Harrison. Studies of a mouse model (maternal immune activation) with stereotyped/repetitive and anxiety-like behaviors indicate that treatment with a member of the human gut microbiota, Bacteroides fragilis, corrects gut barrier (permeability) defects; reduces elevated levels of 4-ethylphenylsulfate, a metabolite seen in the maternal immune activation model that has been causally associated with the animals’ behavioral phenotypes; and ameliorates some behavioral effects. These observations highlight the importance of further exploration of potentially co-evolved relationships between the microbiota and host behavior.


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InternalMed_Harrison. Immune Function Many foundational studies have shown that the gut microbiota plays a key role in the maturation of the innate as well as the adaptive components of the immune system. The intestinal epithelium, which is composed of four principal cell lineages (enterocytes plus goblet, Paneth, and enteroendocrine cells), acts as a physical and functional barrier to microbial penetration. Goblet cells produce mucus that overlies the epithelium, where it forms two layers: an outer (luminal-facing) looser layer that harbors microbes and a denser lower layer that normally excludes microbes. Members of the Paneth cell lineage reside at the base of crypts of Lieberkühn and secrete antimicrobial peptides. Studies in mice have demonstrated that Paneth cells directly sense the presence of a microbiota through expression of the signaling adaptor protein MyD88, which helps transduce signals to host cells upon recognition of microbial products through Toll-like receptors (TLRs). This recognition


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InternalMed_Harrison. through expression of the signaling adaptor protein MyD88, which helps transduce signals to host cells upon recognition of microbial products through Toll-like receptors (TLRs). This recognition drives expression of antibacterial products (e.g., the lectin RegIIIγ) that act to prevent microbial translocation across the gut mucosal barrier.


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InternalMed_Harrison. The intestine is enriched for B cells that produce IgA, which is secreted into the lumen; there it functions to exclude microbes from crossing the mucosal barrier and to restrict dissemination of food antigens. The microbiota plays a key role in development of an IgA response: germ-free mice display a marked reduction in IgA+ B cells. The absence of a normal IgA response can lead to a massive increase in bacterial load. B cell–derived IgA that targets specific members of the gut microbiota plays an important role in preventing activation of microbiota-specific T cells.


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InternalMed_Harrison. Gut bacterial species elicit development of protective TH17 and TH1 responses that help ward off pathogen attack. Members of the microbiota also promote the development of a specialized population of CD4+ T cells that prevent unwarranted inflammatory responses. These regulatory T cells (Tregs) are characterized by expression of the transcription factor forkhead box P3 (FOXP3) and by expression of other cell-surface markers. There is a paucity of Tregs in the colonic lamina propria of germ-free mice. Specific members of the microbiota—including a consortium of Clostridium strains isolated from the mouse and human gut as well as several human-gut Bacteroides species —expand the Treg compartment and enhance immunosuppressive functions.


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InternalMed_Harrison. The microbiota is a key trigger in the development of inflammatory bowel disease (IBD) in mice that harbor mutations in genes associated with IBD risk in humans. Moreover, components of the gut microbiota can modify the activity of the immune system to ameliorate or prevent IBD. Mice containing a mutant ATG16L1 allele linked to Crohn’s disease are particularly susceptible to IBD. Upon infection with mouse norovirus and treatment with dextran sodium sulfate, expression of a hypomorphic ATG16L1 allele leads to defects in small-intestinal Paneth cells and renders mice significantly more susceptible to ileitis than are wild-type control animals. This process is dependent on the gut microbiota and highlights how the intersection of host genetics, infectious agents, and the microbiota can lead to severe immune pathology; i.e., the pathogenic potential of a microbiota may be context-dependent, requiring a confluence of factors. An important observation is that members of the gut microbiota,


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InternalMed_Harrison. to severe immune pathology; i.e., the pathogenic potential of a microbiota may be context-dependent, requiring a confluence of factors. An important observation is that members of the gut microbiota, including B. fragilis or members of Clostridium, prevent the severe inflammation that develops in mouse models mimicking various aspects of human IBD.


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InternalMed_Harrison. The gut microbiota has been implicated in promoting immunopathology outside of the intestine. Multiple sclerosis develops in conventionally raised mice whose CD4+ T cell compartment is reactive to myelin oligodendrocyte protein; their germ-free counterparts are completely protected from development of multiple sclerosis–like symptoms. This protection is reversed by colonization with a gut microbiota from conventionally raised animals.


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InternalMed_Harrison. Inflammasomes are cytoplasmic multiprotein complexes that sense stress and damage-associated patterns. Mice deficient in NLRP6, a component of the inflammasome, are more susceptible to colitis induced by administration of dextran sodium sulfate. This enhanced susceptibility is associated with alterations in the gut microbiota of these animals relative to that of wild-type controls. Mice are coprophagic, and co-housing of NLRP6-deficient mice with wild-type mice is sufficient to transfer the enhanced susceptibility to colitis induced by dextran sodium sulfate. Similar findings have been reported for mice deficient in the inflammasome adaptor ASC (apoptosis-associated speck-like protein containing a caspase recruitment domain). ASC-deficient mice are more susceptible to the development of a model of nonalcoholic steatohepatitis. This susceptibility is associated with alterations in gut microbiota structure and can be transferred to wild-type animals by co-housing.


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InternalMed_Harrison. Obesity and Diabetes Germ-free mice are resistant to diet-induced obesity. Genetically obese ob/ob mice have gut microbial-community structures that are profoundly altered from those in their lean wild-type (+/+) and heterozygous +/ob littermates. Transplantation of the ob/ob mouse microbiota into wild-type germ-free animals transmits an increased-adiposity phenotype not seen in mice receiving microbiota transplants from +/+ and +/ob littermates. These differences are not attributable to differences in food consumption but rather are associated with differences in microbial community metabolism. Roux-en-Y gastric bypass produces pronounced decreases in weight and adiposity as well as improved glucose metabolism—changes that are not ascribable simply to decreased caloric intake or reduced nutrient absorption. 16S rRNA analyses have documented that changes in the gut microbiota after this surgery are conserved among mice, rats, and humans; animal studies have demonstrated these changes


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InternalMed_Harrison. nutrient absorption. 16S rRNA analyses have documented that changes in the gut microbiota after this surgery are conserved among mice, rats, and humans; animal studies have demonstrated these changes along the length of the gut but most prominently downstream of the site of surgical manipulation of the bowel. Notably, transplantation of the gut microbiota from mice that have undergone Roux-en-Y gastric bypass to germ-free mice that have not had this surgery produces reductions in weight and adiposity not seen in recipients of microbiotas from mice that underwent sham surgery.


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InternalMed_Harrison. The gut microbiota confers protection against the development of type 1 diabetes mellitus in the non-obese diabetic (NOD) mouse model. Disease incidence is significantly lower in conventionally raised male NOD mice than in their female counterparts, while germ-free males are as susceptible as their female counterparts. Castration of males increases disease incidence, while androgen treatment of females provides protection. Transfer of the gut microbiota from adult male NOD mice to female NOD weanlings is sufficient to reduce the severity of disease relative to that among females receiving a microbiota from an adult female or an unmanipulated female. The blocking of protection by treatment with flutamide highlights a functional role for testosterone signaling in this microbiota-mediated protection against type 1 diabetes.


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InternalMed_Harrison. NOD mice deficient in MyD88, a key component of the TLR signaling pathway, do not develop diabetes and exhibit increased relative abundance of members of the family-level taxon Lactobacillaceae. Consistent with these findings, investigators have documented lower levels of representation of members of the genus Lactobacillus in children with type 1 diabetes than in healthy controls. Components of lactobacilli have been shown to promote gut barrier integrity. Studies in various animal models indicate that translocation of bacterial components, including bacterial lipopolysaccharides, across a leaky gut barrier triggers low-grade inflammation, which contributes to insulin resistance. Mice deficient in TLR5 exhibit alterations in the gut microbiota and hyperphagia, and they develop features of metabolic syndrome, including hypertension, hyperlipidemia, insulin resistance, and increased adiposity.


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InternalMed_Harrison. The gut microbiota regulates biosynthesis as well as metabolism of host-derived products; these products can signal through host receptors to shape host physiology. An example of this symbiosis is provided by bile acids, which direct metabolic effects that are largely mediated through the farnesoid X receptor (FXR, also known as NR1H4). In leptin-deficient mice, FXR deficiency protects against obesity and improves insulin sensitivity. In mice with diet-induced obesity that are subjected to vertical sleeve gastrectomy, the surgical procedure results in elevated levels of circulating bile acids, changes in the gut microbiota, weight loss, and improved glucose homeostasis. However, weight reduction and improved insulin sensitivity are mitigated in animals with engineered FXR-deficiency. Xenobiotic Metabolism Evidence is accumulating that pharmacogenomic studies need to consider the gene repertoire present in our


InternalMed_Harrison

InternalMed_Harrison. Xenobiotic Metabolism Evidence is accumulating that pharmacogenomic studies need to consider the gene repertoire present in our H. sapiens genome as well as that in our microbiomes. For example, digoxin is inactivated by the human gut bacterium Eggerthella lenta, but only by strains with a cytochrome-containing operon. Expression of this operon is induced by digoxin and inhibited by arginine. Studies in gnotobiotic mice established that dietary protein affects (reduces) microbial metabolism of digoxin, with corresponding alterations in levels of the drug in both serum and urine. These findings reinforce the need to consider strain-level diversity in the gut microbiota when examining interpersonal variations in the metabolism of orally administered drugs.


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InternalMed_Harrison. Characterizing the Effects of the Human Microbiota on Host Biology in Mice and Humans Questions about the relationship between human microbial communities and health status can be posed in the following general format: Is there a consistent configuration of the microbiota definable in the study population that is associated with a given disease state? How is the configuration affected by remission/relapse or by treatment? If a reconfiguration does occur with treatment, is it durable? How is host biology related to the configuration or reconfiguration? What is the effect size? Are correlations robust to individuals from different families and communities representing different ages, geographic locales, and lifestyles?


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InternalMed_Harrison. As in all studies involving human microbial ecology, the issue of what constitutes a suitable reference control is extremely important. Should we choose the person himself or herself, family members, or ageor gender-matched individuals living in the same locale and representing similar cultural traditions? Critically, are the relationships observed between microbial community structure and expressed functions a response to disease state (i.e., side effects of other processes), or are they a contributing cause? In this sense, we are challenged to evolve a set of Koch’s postulates that can be applied to whole microbial communities or components of communities rather than just to a single purified organism. As in other circumstances in which experiments to determine causality of human disease are difficult or unethical, Hill’s criteria, which examine the strength, consistency, and biologic plausibility of epidemiologic data, can be useful.


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InternalMed_Harrison. Sets of monoand dizygotic twins and their family members represent a valuable resource for initially teasing out relationships between environmental exposures, genotypes, and our own microbial ecology. Similarly, monozygotic twins discordant for various disease states enhance the ability to determine whether various diseases can be linked to a person’s microbiota and microbiome. A twin-pair sampling design rather than a conventional unrelated case–control design has advantages owing to the pronounced between-family variability in microbiota/microbiome composition and the potential for multiple states of a community associated with disease. Transplantation of a microbiota from suitable human donor controls representing different disease states and communities (e.g., twins discordant for a disease) to germ-free mice is helpful in establishing a causal role for the com-86e-9 munity in pathogenesis and for providing insights relevant to underlying mechanisms. In addition, transplantation


InternalMed_Harrison

InternalMed_Harrison. disease) to germ-free mice is helpful in establishing a causal role for the com-86e-9 munity in pathogenesis and for providing insights relevant to underlying mechanisms. In addition, transplantation provides a preclinical platform for identifying next-generation probiotics, prebiotics, or combinations of the two (synbiotics). Obesity and obesity-associated metabolic dysfunction illustrate these points.


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InternalMed_Harrison. The gut microbiotas (and microbiomes) of obese individuals are significantly less diverse than those of lean individuals; the implication is that there may be unfilled niches (unexpressed functions) that contribute to obesity and its associated metabolic abnormalities. Le Chatelier and colleagues observed a bimodal distribution of gene abundance in their analysis of 292 fecal microbiomes: low-gene-count (LGC) individuals averaged 380,000 microbial genes per gut microbiome, while high-gene-count (HGC) individuals averaged 640,000 genes. LGC individuals had an increased risk for type 2 diabetes and other metabolic abnormalities, whereas the HGC group was metabolically healthy. When gene content was used to identify taxa that discriminated HGC and LGC individuals, the results revealed associations between anti-inflammatory bacterial species such as Faecalibacterium prausnitzii and the HGC group and between proinflammatory species such as Ruminococcus gnavus and the LGC group. LGC


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InternalMed_Harrison. associations between anti-inflammatory bacterial species such as Faecalibacterium prausnitzii and the HGC group and between proinflammatory species such as Ruminococcus gnavus and the LGC group. LGC microbiomes had significantly greater representation of genes assigned to tricarboxylic acid cycle modules, peroxidases, and catalases—an observation suggesting a greater capacity to handle oxygen exposure and oxidative stress; HGC microbiomes were enriched in genes involved in the production of organic acids, including lactate, propionate, and butyrate— a result suggesting increased fermentative capacity.


InternalMed_Harrison

InternalMed_Harrison. Transplantation of an uncultured fecal microbiota from twins stably discordant for obesity or of bacterial culture collections generated from their microbiota transmits their discordant adiposity phenotypes as well as obesity-associated metabolic abnormalities to recipient germ-free mice. Co-housing of the recipient coprophagic gnotobiotic mice results in invasion of specific bacterial species from the transplanted lean twin’s culture collection into the guts of cage mates harboring the obese twin’s culture collection (but not vice versa), thereby preventing the latter animals from developing obesity and its associated metabolic abnormalities. It is noteworthy that invasion and prevention of obesity and metabolic phenotypes are dependent on the type of human diets fed to animals: prevention is associated with a diet low in saturated fats and high in fruit and vegetable content, but not with a diet high in saturated fats and low in fruit and vegetable content.


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InternalMed_Harrison. This approach provides evidence for a causal role for the microbiota in obesity and its attendant metabolic abnormalities. It also provides a method for defining unoccupied niches in disease-associated microbial communities, the role of dietary components in determining how these niches can be filled by human gut–derived bacterial taxa, and the effects of such occupancy on microbial and host metabolism. It also provides a way to identify health-promoting diets and next-generation probiotics representing naturally occurring members of our indigenous microbial communities that are well adapted to persist in a given body habitat.


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InternalMed_Harrison. A key to this approach is the ability to harvest a microbial community from a donor representing a physiology, disease state, lifestyle, or geography of interest; to preserve the donor’s community by freezing it; and then to resurrect and replicate it in multiple recipient gnotobiotic animals that can be reared under conditions where environmental and host variables can be controlled and manipulated to a degree not achievable in clinical studies. Since these mice can be followed as a function of time prior to and after transplantation, in essence, a snapshot of a donor’s community can be converted into a movie. Transplantation of intact uncultured human (fecal) microbiota samples from multiple donors representing the phenotype of interest, with administration of the donors’ diets (or derivatives of those diets) to different groups of mice, is one way to assess whether transmissible responses are shared features of the microbiota or are highly donor specific. A second step is to


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InternalMed_Harrison. derivatives of those diets) to different groups of mice, is one way to assess whether transmissible responses are shared features of the microbiota or are highly donor specific. A second step is to determine whether the culturable component of a representative microbiota sample can transmit the phenotype(s) observed with the intact uncultured sample. Possession of a collection of cultured organisms that have co-evolved in a given donor’s body habitat sets the stage


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InternalMed_Harrison. Chapter 86e The Human Microbiome for the selection of subsets of the collection for testing in gnotobiotic mice, the determination of which members are responsible for effecting the phenotype, and the elucidation of the mechanisms underlying these effects. The models used may inform the design and interpretation of clinical studies of the very individuals and populations whose microbiota are selected for creating these models. Human-to-human fecal microbiota transplantation (FMT) is currently the most direct way to establish proof-of-concept for a causal role for the microbiota in disease pathogenesis. A human donor’s feces are provided to a recipient via nasogastric tube or another technique. Numerous small trials have documented the effects of FMT from healthy donors to recipients with diseases ranging from C. difficile infection to Crohn’s disease, ulcerative colitis, and type 2 diabetes. Only a few of these studies have used a double-blind, placebo-controlled design.


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InternalMed_Harrison. In a double-blind, controlled trial involving men 21–65 years old with a body mass index of >30 kg/m2 and documented insulin resistance, FMT was performed using a microbiota from metabolically healthy lean donors or from the study participants themselves. A microbiota from lean donors significantly improved peripheral insulin sensitivity over that in controls. This change was associated with an increase in the relative abundance of the butyrate-producing bacteria related to Roseburia intestinalis (in the feces) and Eubacterium hallii (in the small intestine).


InternalMed_Harrison

InternalMed_Harrison. The efficacy of FMT for the treatment of recurrent C. difficile infection has been assessed in a number of small trials. One unblinded, placebo-controlled trial assessed the use of FMT in 42 patients with recurrent C. difficile infection (defined as at least one relapse after treatment with vancomycin or metronidazole for ≥10 d). Patients were pretreated with oral vancomycin. The experimental group then received FMT via nasoduodenal tube from healthy volunteer donors (<60 years of age) selected from the community. Controls underwent sterile lavage or received oral vancomycin alone. In 10 weeks of follow-up, infection was cured (with cure defined as three negative fecal tests for C. difficile toxin) in 81% of patients in the FMT group (13 of 16) but in only 23% (3 of 13) in the bowel-lavage control arm and 31% (4 of 13) in the vancomycin-only group. Metagenomic analysis of microbiota samples collected before and after treatment revealed an increased representation of Bacteroidetes and


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InternalMed_Harrison. control arm and 31% (4 of 13) in the vancomycin-only group. Metagenomic analysis of microbiota samples collected before and after treatment revealed an increased representation of Bacteroidetes and Clostridium clusters IV and XIVa, along with a 100-fold decrease in the relative abundance of Proteobacteria, in the FMT group.


InternalMed_Harrison

InternalMed_Harrison. A meta-analysis of FMT in C. difficile infection examined 20 case-series publications, 15 case reports, and the one unblinded study described above. All but one of these studies used fresh (not frozen) fecal samples. Donor selection varied, although most donors were family members or relatives and most studies excluded donors who had recently received antibiotics. It is noteworthy that the concentrations of infused donor feces varied widely (i.e., from 5 g to 200 g, resuspended in 10–500 mL); these fecal suspensions were introduced at different sites along the gastrointestinal tract, including the stomach and points throughout the small intestine and colon. Resolution of infection, which was frequently assessed on the basis of symptom resolution (with C. difficile toxin testing rarely performed), was documented in 87% (467) of 536 treated patients. The most common adverse events reported were diarrhea (94% of cases) and abdominal cramps (31%) on the day of infusion. The meta-analysis


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InternalMed_Harrison. was documented in 87% (467) of 536 treated patients. The most common adverse events reported were diarrhea (94% of cases) and abdominal cramps (31%) on the day of infusion. The meta-analysis was limited to clinical outcomes and did not specifically address the role of the microbiota in disease resolution (e.g., the extent of invasion of donor taxa; their persistence; or the long-term effects of transplantation on various facets of host biology, which generally have not been evaluated).


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InternalMed_Harrison. Sober and thoughtful consideration needs to be applied to the therapeutic use of FMT, which represents an early and rudimentary approach to microbiota manipulation that very likely will be replaced by administration of defined collections of sequenced, cultured members of the human microbiota (probiotic consortia). A number of published reports on FMT have garnered significant public attention. This attention, coupled with an increasing public appreciation of the beneficial nature of our interactions with microbes, demands that the precautionary principle be honored and that risks versus benefits of such interventions be carefully evaluated.


InternalMed_Harrison

InternalMed_Harrison. To date, most FMT trials have failed to define (or have differed in) significant confounders, including (1) the criteria used for donor sample selection; (2) the methods used for donor sample preparation and characterization as well as the decision about whether or not to create a repository for donor and recipient samples that will permit retrospective analyses (and meta-analyses for given disease states); the development of minimal standards for assessing the invasion of recipient gut communities by taxa from donor microbiota (using microbial source-tracking methods) as well as the timing, duration, nature, and breadth of sampling of the recipient as a function of transplantation; (4) the adoption of minimal standards for collection of patients’ clinical data (e.g., age, diet, antibiotic use) and the establishment of databases for entering these data (including use of a defined vocabulary for annotating the clinical data); and (5) the development of standards for informed consent in


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InternalMed_Harrison. use) and the establishment of databases for entering these data (including use of a defined vocabulary for annotating the clinical data); and (5) the development of standards for informed consent in lieu of knowledge of the longterm effects of the procedure. The regulatory landscape is evolving. The U. S. Food and Drug Administration recently issued an enforcement policy specifically addressing the use of FMT for the treatment of recurrent C. difficile infection; this policy indicates that the agency intends to “exercise enforcement discretion regarding the investigational new drug (IND) requirements for the use of FMT to treat


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InternalMed_Harrison. C. difficile infection not responding to standard therapies,” but it does not waive IND requirements for other FMT studies.


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InternalMed_Harrison. The design of human microbiome studies is rapidly evolving, in part because the data are highly multivariate, are compositional, and do not meet distributional assumptions of standard statistical tests such as analysis of variance. Consequently, the proper number of subjects to enroll and the proper populations to target remain to be established. One useful approach is to review published studies and ask whether the reported conclusion could be obtained with fewer subjects (sample rarefaction) and/or fewer sequencing reads from SSU rRNA genes, whole-community DNA (microbiomes), or expressed community mRNA (metatranscriptomes) per subject (sequence rarefaction). A common yet critical problem to avoid is under-sampling of the types of objects under study. For example, if the goal is to compare factors applying to individuals (e.g., individual diet), then dozens of individuals in each clinical category may be needed. If the goal is to compare factors applying to populations (e.g.,


InternalMed_Harrison

InternalMed_Harrison. compare factors applying to individuals (e.g., individual diet), then dozens of individuals in each clinical category may be needed. If the goal is to compare factors applying to populations (e.g., demographic properties), then many populations may be needed.


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InternalMed_Harrison. Another key issue is whether the effect size to be studied, especially in meta-analysis, is greater than or less than technical effects. As noted above, different PCR primers will lead to different readouts of the taxonomy of a microbial community; these differences are, for example, greater than the differences between lean and obese subjects’ fecal microbiota but less than the difference between fecal communities in newborns and adults.


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InternalMed_Harrison. A central challenge in human microbiome research is establishing the extent to which diagnostic tests and therapeutic approaches are generalizable. This challenge is illustrated by studies of the capacities of gut microbiomes to metabolize orally administered drugs. The results could be very informative for the pharmaceutical industry as it seeks new and more accurate ways to predict bioavailability and toxicity. However, these studies should prompt consideration of the fact that many clinical trials are outsourced to countries where trial participants have diets and microbial community structures that differ from those of the intended initial recipients of the (marketed) drug. Capture and preservation of the wide range of microbial diversity present in different human populations—and thus of the capacity of our microbial communities to catalyze elaborate and in many respects uncharacterized biotransformations—represent potentially fertile ground for the discovery of new drugs (and


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InternalMed_Harrison. of the capacity of our microbial communities to catalyze elaborate and in many respects uncharacterized biotransformations—represent potentially fertile ground for the discovery of new drugs (and new industrial processes of societal value). The chemical entities that our microbial communities have evolved to synthesize in order to support their mutually beneficial relationships and the human genes that these chemotypes influence may become new classes of drugs and new targets for drug discovery, respectively. Therefore, characterization of groups of individuals living in countries that are undergoing rapid transformations in cultural traditions and socioeconomic conditions and are witnessing the emergence of a variety of diseases associated with increasingly Western lifestyles (globalization) is a timely challenge. Birth cohort studies (including studies of twins) initiated every 10 years in these countries may be able to capture the impact of globalization, including changing diets,


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InternalMed_Harrison. is a timely challenge. Birth cohort studies (including studies of twins) initiated every 10 years in these countries may be able to capture the impact of globalization, including changing diets, on human microbial ecology.


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InternalMed_Harrison. Although microbiome-associated diagnostics and therapeutics provide new and exciting dimensions for personalized medicine, attention must be paid to the potentially broad societal impact of this work. For example, studies of the human gut microbiome are likely to have a disruptive effect on current views of human nutrition, enhancing appreciation of how food and the metabolic output of interactions of dietary components with the microbiota are intimately connected to myriad features of human biology. Underlying the efforts to elucidate the relations among food, the microbiome, and human nutrition is a need to proactively develop materials for educational outreach with a narrative and vocabulary that is understandable to broad and varied consumer populations representing different cultural traditions and widely ranging degrees of scientific literacy. The results have the potential to catalyze efforts to integrate agricultural policies and practice, food production, and nutritional


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InternalMed_Harrison. traditions and widely ranging degrees of scientific literacy. The results have the potential to catalyze efforts to integrate agricultural policies and practice, food production, and nutritional recommendations for consumer populations representing different ages, geographic locales, and states of health.


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InternalMed_Harrison. Defining our metagenome (the genes embedded in our H. sapiens genome plus those in our microbiome) will likely lead to an entirely new level of refinement in our description of self, our genetic evolution, 86e-11 our postnatal development, the microbial legacy of our connection to family, and the consequences of personal lifestyle choices. While this information can help us understand the origins of certain yet unexplained health disparities, care must be taken to avoid stigmatization of individuals or groups of individuals having different cultural norms, belief systems, or behaviors. In partnership with human microbiome researchers, anthropologists need to examine the impact of studies of the human microbiome on the participants, assessing how this field and participants’ cultural traditions interact to affect these individuals’ perceptions about the natural world, the forces that affect their lives, and their connections to one another within the context of family and community.


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InternalMed_Harrison. Studies of human microbial ecology are an important manifestation of progress in the genome sciences, represent a timely step in our quest to achieve a better understanding of our place in the natural world, and reflect the evolving focus of twenty-first-century medicine on disease prevention, new definitions of health, new ways to determine the origins of individual biologic differences, and new approaches to evaluating the impact of changes in our lifestyles and biosphere on our biology. As microbiome-directed diagnostics and therapeutics emerge, we must be sensitive to the societal impact of this work.


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InternalMed_Harrison. Chapter 86e The Human Microbiome that challenge the discipline. Biologists study the experimental response of a variable of interest in a cell or organism while holding all other variables constant. In this way, it is possible to dissect the individual components of a biologic system and assume that a thorough understanding of a specific component (e.g., an enzyme or a transcription factor) will provide sufficient insight to explain the global behavior of that system (e.g., a metabolic pathway or a gene network, respectively). Biologic systems are, however, much more complex than this approach assumes and manifest behaviors that frequently (if not invariably) cannot be predicted from knowledge of their component parts characterized in isolation. Growing recognition of this shortcoming of conventional biologic research has led to the development of a new discipline, systems biology, which is defined as the holistic study of living organisms or their cellular or molecular network


InternalMed_Harrison

InternalMed_Harrison. of conventional biologic research has led to the development of a new discipline, systems biology, which is defined as the holistic study of living organisms or their cellular or molecular network components to predict their response to perturbations. Concepts of systems biology can be applied readily to human disease and therapy and define the field of systems pathobiology, in which genetic or environmental perturbations produce disease and drug perturbations restore normal system behavior.


InternalMed_Harrison

InternalMed_Harrison. Systems biology evolved from the field of systems engineering in which a linked collection of component parts constitute a network whose output the engineer wishes to predict. The simple example of an electronic circuit can be used to illustrate some basic systems engineering concepts. All the individual elements of the circuit—resistors, capacitors, transistors—have well-defined properties that can be characterized precisely. However, they can be linked (wired or configured) in a variety of ways, each of which yields a circuit whose response to voltage applied across it is different from the response of every other configuration. To predict the circuit’s (i.e., system’s) behavior, the engineer must study its response to perturbation (e.g., voltage applied across it) holistically rather than its individual components’ responses to that perturbation. Viewed another way, the resulting behavior of the system is greater than (or different from) the simple sum of its parts, and systems


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InternalMed_Harrison. than its individual components’ responses to that perturbation. Viewed another way, the resulting behavior of the system is greater than (or different from) the simple sum of its parts, and systems engineering utilizes rigorous mathematical approaches to predict these complex, often nonlinear, responses. By analogy to biologic systems, one can reason that detailed knowledge of a single enzyme in a metabolic pathway or of a single transcription factor in a gene network will not provide sufficient detail to predict the output of that metabolic pathway or transcriptional network, respectively. Only a systems-based approach will suffice.


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InternalMed_Harrison. It has taken biologists a long time to appreciate the importance of systems approaches to biomedical problems. Reductionism has reigned supreme for many decades, largely because it is experimentally and analytically simpler than holism, and because it has provided insights into biologic mechanisms and disease pathogenesis that have led to successful therapies. However, reductionism cannot solve all biomedical problems. For example, the so-called off-target effects of new drugs that frequently limit their adoption likely reflect the failure of a drug to be studied in holistic context, i.e., the failure to explore all possible actions aside from the principal target action for which it was developed. Other approaches to understanding biology therefore are clearly needed. With the growing body of genomic, proteomic, and metabolomic data sets in which dynamic changes in the expression of many genes and many metabolites are recorded after a perturbation and with the growth of rigorous


InternalMed_Harrison

InternalMed_Harrison. body of genomic, proteomic, and metabolomic data sets in which dynamic changes in the expression of many genes and many metabolites are recorded after a perturbation and with the growth of rigorous mathematical approaches to analyzing those changes, the stage has been set for applying systems engineering principles to modern biology.


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InternalMed_Harrison. Physiologists historically have had more of a (bio)engineering perspective on the conduct of their studies and have been among the first systems biologists. Yet, with few exceptions, they, too, have focused on comparatively simple physiologic systems that are tractable using 87e-1 conventional reductionist approaches. Efforts at integrative modeling of human physiologic systems, as first attempted by Guyton for blood pressure regulation, represent one application of systems engineering to human biology. These dynamic physiologic models often focus on the acute response of a measurable physiologic parameter to a system perturbation, and do so from a classic analytic perspective in which all the conventional physiologic determinants of the output parameter are known and can be modeled quantitatively.


InternalMed_Harrison

InternalMed_Harrison. Until recently, molecular systems analysis has been limited owing to inadequate knowledge of the molecular determinants of a biologic system of interest. Although biochemists have approached metabolic pathways from a systems perspective for over 50 years, their efforts have been limited by the inadequacy of key information for each enzyme (KM, kcat, and concentration) and substrate (concentration) in the pathway. With increasingly rich molecular data sets available for systems-based analyses, including genomic, transcriptomic, proteomic, and metabolomic data, biochemists are now poised to use systems biology approaches to explore biologic and pathobiologic phenomena.


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InternalMed_Harrison. To understand how best to apply the principles of systems biology to human biomedicine, it is necessary to review briefly the building blocks of any biologic system and the determinants of system complexity. All systems can be analyzed by defining their static topology (architecture) and their dynamic (i.e., time-dependent) response to perturbation. In the discussion that follows, system properties are described that derive from the consequences of topology (form) or dynamic response (function). Any system of interacting elements can be represented schematically as a network in which the individual elements are depicted as nodes and their connections are depicted as links. The nature of the links among nodes reflects the degree of complexity of the system. Simple systems are those in which the nodes are linearly linked with occasional feedback or feedforward loops modulating system throughput in highly predictable ways. By contrast, complex systems are nodes that are linked in more


InternalMed_Harrison

InternalMed_Harrison. the nodes are linearly linked with occasional feedback or feedforward loops modulating system throughput in highly predictable ways. By contrast, complex systems are nodes that are linked in more complicated, nonlinear networks; the behavior of these systems by definition is inherently more difficult to predict owing to the nature of the interacting links, the dependence of the system’s behavior on its initial conditions, and the inability to measure the overall state of the system at any specific time with great precision. Complex systems can be depicted as a network of lower-complexity interacting components or modules, each of which can be reduced further to simpler analyzable canonical motifs (such as feedback and feedforward loops, or negative and positive autoregulation); however, a central property of complex systems is that simplifying their structures by identifying and characterizing the individual nodes and links or even simpler substructures does not necessarily yield a


InternalMed_Harrison

InternalMed_Harrison. a central property of complex systems is that simplifying their structures by identifying and characterizing the individual nodes and links or even simpler substructures does not necessarily yield a predictable understanding of a system’s behavior. Thus, the functioning system is greater than (or different from) the sum of its individual, tractable parts.


InternalMed_Harrison

InternalMed_Harrison. Defined in this way, most biologic systems are complex systems that can be represented as networks whose behaviors are not readily predictable from simple reductionist principles. The nodes, for example, can be metabolites that are linked by the enzymes that cause their transformations, transcription factors that are linked by the genes whose expression they influence, or proteins in an interaction network that are linked by cofactors that facilitate interactions or by thermodynamic forces that facilitate their physical association. Biologic systems typically are organized as scale-free, rather than stochastic, networks of nodes. Scale-free networks are those in which a few nodes have many links to other nodes (highly linked nodes, or hubs) but most nodes have only a few links (weakly linked nodes). The term scale-free refers to the fact that the connectivity of nodes in the network is invariant with respect to the size of the network. This is quite different from two other common


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InternalMed_Harrison. linked nodes). The term scale-free refers to the fact that the connectivity of nodes in the network is invariant with respect to the size of the network. This is quite different from two other common network architectures: random (Poisson) and exponential distributions. Scale-free networks can be mathematically described by a power law that defines the probability of the number of


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InternalMed_Harrison. Chapter 87e Network Medicine: Systems Biology in Health and Disease FIGuRE 87e-1 Network representations and their distributions. A random network is depicted on the left, and its Poisson distribution of the number of nodal connections (k) is shown in the graph below it. A scale-free network is depicted on the right, and its power law distribution of the number of nodal connections (k) is shown in the graph below it. Highly connected nodes (hubs) are lightly shaded. links per node (P[k] = k−[γ], where k is the number of links per node and γ is the slope of the log P[k] versus log[k] plot); this unique property of most biologic networks is a reflection of their self-similarity or fractal nature (Fig. 87e-1).


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InternalMed_Harrison. There are unique properties of scale-free biologic systems that reflect their evolution and promote their adaptability and survival. Biologic networks likely evolved one node at a time in a process in which new nodes are more likely to link to a highly connected node than to a sparsely connected node. Furthermore, scale-free networks can become sparsely linked to one another, yielding more complex, modular scale-free topologies. This evolutionary growth of biologic networks has three important properties that affect system function and survival. First, this scale-free addition of new nodes promotes system redundancy, which minimizes the consequences of errors and accommodates adverse perturbations to the system robustly with minimal effects on critical functions (unless the highly connected nodes are the focus of the perturbation). Second, this resulting network redundancy provides a survival advantage to the system. In complex gene networks, for example, mutations or polymorphisms in


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InternalMed_Harrison. nodes are the focus of the perturbation). Second, this resulting network redundancy provides a survival advantage to the system. In complex gene networks, for example, mutations or polymorphisms in weakly linked genes account for biodiversity and biologic variability without disrupting the critical functions of the system; only mutations in highly linked (essential) genes (hubs) can shut down the system and cause embryonic lethality. Third, scale-free biologic systems facilitate the flow of information (e.g., metabolite flux) across the system compared with randomly organized biologic systems; this so-called “small-world” property of the system (in which the clustered nature of the highly linked hubs defines a local neighborhood within the network that communicates through weaker, less frequent links to other clusters) minimizes the energy cost for the dynamic action of the system (e.g., minimizes the transition time between states in a metabolic network).


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InternalMed_Harrison. These basic organizing principles of complex biologic systems lead to three unique properties that require emphasis. First, biologic systems are robust, which means that they are quite stable in response to most changes in external conditions or internal modification. Second, a corollary to the property of robustness is that complex biologic systems are sloppy, which means that they are insensitive to changes in external conditions or internal modification except under certain uncommon conditions (i.e., when a hub is involved in the change). Third, complex biologic systems exhibit emergent properties, which means that they manifest behaviors that cannot be predicted from the reductionist principles used to characterize their component parts. Examples of emergent behavior in biologic systems include spontaneous, self-sustained oscillations in glycolysis; spiral and scroll waves of depolarization in cardiac tissue that cause reentrant arrhythmias; and self-organizing patterns in


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InternalMed_Harrison. systems include spontaneous, self-sustained oscillations in glycolysis; spiral and scroll waves of depolarization in cardiac tissue that cause reentrant arrhythmias; and self-organizing patterns in biochemical systems governed by diffusion and chemical reaction.


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InternalMed_Harrison. The principles of systems biology have been applied to complex pathologic processes with some early successes. The key to these applications is the identification of emergent properties of the system under study in order to define novel, otherwise unpredictable (i.e., from the reductionist perspective) methods for regulating the system’s response. Systems biology approaches have been used to characterize epidemics and ways to control them, taking advantage of the scale-free properties of the network of infected individuals that constitute the epidemic. Through the use of a systems analysis of a neural protein-protein interaction network, unique disease-modifying proteins have been identified that are common to a wide range of cerebellar neurodegenerative disorders causing inherited ataxias. Systems analysis and disease network construction of a pulmonary arterial hypertension network led to the identification of a unique disease module involving a pathway governed by microRNA21.


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InternalMed_Harrison. Systems analysis and disease network construction of a pulmonary arterial hypertension network led to the identification of a unique disease module involving a pathway governed by microRNA21. Systems biology models have been used to dissect the dynamics of the inflammatory response using oscillatory changes in the transcription factor nuclear factor (NF) κB as the system output. Systems biology principles also have been used to predict the development of an idiotypy–anti-idiotypy antibody network, describe the dynamics of species growth in microbial biofilms, and analyze the innate immune response. In each of these examples, a systems (patho)biology approach provided insights into the behavior of these complex systems that could not have been recognized with conventional scientific reductionism.


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InternalMed_Harrison. A unique application of systems biology to biomedicine is in the area of drug development. Conventional drug development involves identifying a potential target protein and then designing or screening compounds to identify those that inhibit the function of that target. This reductionist analysis has identified many potential drug targets and drugs, yet only when a drug is tested in animal models or humans are the systems consequences of the drug’s action revealed; not uncommonly, so-called off-target effects may become apparent and be sufficiently adverse for researchers to cease development of the agent. A good example of this problem is the unexpected outcomes of the vitamin B–based regimens for lowering homocysteine levels. In these trials, plasma homocysteine levels were reduced effectively; however, there was no effect of this reduction on clinical vascular endpoints. One explanation for this outcome is that one of the B vitamins in the regimen, folate, has a panoply of effects


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InternalMed_Harrison. however, there was no effect of this reduction on clinical vascular endpoints. One explanation for this outcome is that one of the B vitamins in the regimen, folate, has a panoply of effects on cell proliferation and metabolism that probably offset its homocysteine-lowering benefits, promoting progressive atherosclerotic plaque growth and its consequences for clinical events. In addition to these types of unexpected outcomes exerted through pathways that were not considered ab initio, conventional approaches to drug development typically do not take into consideration the possibility of emergent behaviors of the organism or the metabolic pathway or the transcriptional network of interest. Thus, a systems-based analysis of potential drugs (drug-target network analysis) can benefit the development paradigm both by enhancing the likelihood that a compound of interest will not manifest unforeseen adverse effects and by promoting novel analytic methods for identifying unique control points


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InternalMed_Harrison. paradigm both by enhancing the likelihood that a compound of interest will not manifest unforeseen adverse effects and by promoting novel analytic methods for identifying unique control points or pathways in metabolic or genetic networks that would benefit from drug-based modulation.


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InternalMed_Harrison. SYSTEMS PATHOBIOLOGY AND HuMAN DISEASE CLASSIFICATION: NETWORK MEDICINE Perhaps most important, systems pathobiology can be used to revise and refine the definition of human disease. The classification of human disease used in this and all medical textbooks derives from the correlation between pathologic analysis and clinical syndromes that began in the nineteenth century. Although this approach has been very successful, serving as the basis for the development of many effective therapies, it has major shortcomings. Those shortcomings include a lack of sensitivity in defining preclinical disease, a primary focus on overtly manifest disease, failure to recognize different and potentially differentiable causes of common late-stage pathophenotypes, and a limited ability to incorporate the growing body of molecular and genetic determinants of pathophenotype into the conventional classification scheme.


InternalMed_Harrison

InternalMed_Harrison. Two examples will illustrate the weakness of simple correlation analyses grounded in the reductionist principle of simplification (Occam’s razor) in defining human disease. Sickle cell anemia, the “classic” Mendelian disorder, is caused by a Val6Gln substitution in the β chain of hemoglobin. If conventional genetic teaching holds, this single mutation should lead to a single phenotype in patients who harbor it (genotype-phenotype correlation). This assumption is, however, false, as patients with sickle cell disease manifest a variety of pathophenotypes, including hemolytic anemia, stroke, acute chest syndrome, bony infarction, and painful crisis, as well as an overtly normal phenotype. The reasons for these different phenotypic presentations include the presence of disease-modifying genes or gene products (e.g., hemoglobin F, hemoglobin C, glucose-6-phosphate dehydrogenase), exposure to adverse environmental factors (e.g., hypoxia, dehydration), and the genetic and environmental


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InternalMed_Harrison. genes or gene products (e.g., hemoglobin F, hemoglobin C, glucose-6-phosphate dehydrogenase), exposure to adverse environmental factors (e.g., hypoxia, dehydration), and the genetic and environmental determinants of common intermediate pathophenotypes (i.e., variations in those generic pathologic mechanisms underlying all human disease—inflammation, thrombosis/hemorrhage, fibrosis, cell proliferation, apoptosis/necrosis, immune response).


InternalMed_Harrison

InternalMed_Harrison. A second example of note is familial pulmonary arterial hypertension. This disorder is associated with over 100 different mutations in three members of the transforming growth factor β (TGF-β) super-family: bone morphogenetic protein receptor-2 (BMPR-2), activin receptor-like kinase-1 (Alk-1), and endoglin. All these different genotypes are associated with a common pathophenotype, and each leads to that pathophenotype by molecular mechanisms that range from haploinsufficiency to dominant negative effects. As only approximately one-fourth of individuals in families that harbor these mutations manifest the pathophenotype, other disease-modifying genes (e.g., 87e-3 the serotonin receptor 5-HT2B, the serotonin transporter 5-HTT), genomic and environmental determinants of common intermediate pathophenotypes, and environmental exposures (e.g., hypoxia, infective agents [HIV], anorexigens) probably account for the incomplete penetrance of the disorder.


InternalMed_Harrison

InternalMed_Harrison. On the basis of these and many other related examples, one can approach human disease from a systems pathobiology perspective in which each “disease” can be depicted as a network that includes the following modules: the primary disease-determining elements of the genome (or proteome, if posttranslationally modified), the disease-modifying elements of the genome or proteome, environmental determinants, and genomic and environmental determinants of the generic intermediate pathophenotypes. Figure 87e-2 graphically depicts these genotype-phenotype relationships as modules for the six common disease types with specific examples for each type. Figure 87e-3 shows a network-based depiction of sickle cell disease using this kind of modular approach.


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InternalMed_Harrison. Goh and colleagues developed the concept of a human disease network (Fig. 87e-4) in which they used a systems approach to characterize the disease-gene associations listed in the Online Mendelian Inheritance in Man database. Their analysis showed that genes linked to similar disorders are more likely to have products that physically associate and greater similarity between their transcription profiles than do genes not associated with similar disorders. In addition, proteins associated with the same pathophenotype are significantly more likely to interact with one another than with other proteins not associated with the pathophenotype. Finally, these authors showed that the great majority of disease-associated genes are not highly connected genes (i.e., not hubs) and are typically weakly linked nodes within the functional periphery of the network in which they operate.


InternalMed_Harrison

InternalMed_Harrison. This type of analysis validates the potential importance of defining disease on the basis of its systems pathobiologic determinants. Clearly, doing this will require a more careful dissection of the molecular elements in the relevant pathways (i.e., more precise molecular pathophenotyping), less reliance on overt manifestations of disease for their classification, and an understanding of the dynamics (not just the static architecture) of the pathobiologic networks that underlie pathophenotypes defined in this way. Figure 87e-5 illustrates the elements of a molecular network within which a disease module is contained. This network is first identified by determining the interactions (physical or regulatory) among the proteins or genes that comprise it (the “interactome”). These interactions then define a topologic module within which exists functional modules (pathways) and disease modules. One approach to constructing this module is illustrated in Fig. 87e-6. Examples of the use of


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InternalMed_Harrison. then define a topologic module within which exists functional modules (pathways) and disease modules. One approach to constructing this module is illustrated in Fig. 87e-6. Examples of the use of this approach in defining novel determinants of disease are given in Table 87e-1.


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InternalMed_Harrison. Chapter 87e Network Medicine: Systems Biology in Health and Disease Hereditary ataxias Many ataxia-causing Lim et al: Cell 125:801proteins share interact-814, 2006 ing partners that affect neurodegeneration Diabetes mellitus Metabolite-protein Wang-Sattler et al: Mol network analysis links Syst Biol 8:615, 2012 three unique metabolite abnormalities in prediabetics to seven type 2 diabetes genes through four enzymes Ebstein-Barr virus infec-Viral proteome exerts its Gulbahce et al: PLoS tion effects through linking One 8:e1002531, 2012 to host interactome Pulmonary arterial Network analysis indi-Parikh et al: Circulation hypertension cates adaptive role for 125:1520-1532, 2012 microRNA 21 in suppressing rho kinase pathway 87e-4 Classsic mendelian disorder: Classic mendelian disorder: Classic mendelian disorder: Example:? Polygenic disorder: Single phenotype Example: Essential hypertension Polygenic disorder: Multiple phenotypes Example: Ischemic heart disease


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InternalMed_Harrison. Example:? Polygenic disorder: Single phenotype Example: Essential hypertension Polygenic disorder: Multiple phenotypes Example: Ischemic heart disease Example: Subacute bacterial endocarditis FIGuRE 87e-2 Examples of modular representations of human disease. D, secondary human disease genome or proteome; E, environmental determinants; G, primary human disease genome or proteome; I, intermediate phenotype; P, pathophenotype. (Reproduced with permission from J Loscalzo et al: Molec Syst Biol 3:124, 2007.)


InternalMed_Harrison

InternalMed_Harrison. As yet another potential consideration, one can argue that disease reflects the later-stage consequences of the predilection of an organ system to manifest a particular intermediate pathophenotype in response to injury. This paradigm reflects a reverse causality view in which a disease is defined as a tendency to heightened inflammation, thrombosis, or fibrosis after an injurious perturbation. Where the process is manifest (i.e., the organ in which it occurs) is less important than that it occurs (with the exception of the organ-specific pathophysiologic consequences that may require acute attention). For example, from this perspective, acute myocardial infarction (AMI) and its consequences are a reflection of thrombosis (in the coronary artery), inflammation (in the acutely injured myocardium), and fibrosis (at the site or sites of cardiomyocyte death). In effect, the major therapies for AMI address these intermediate pathophenotypes (e.g., antithrombotics, statins) rather than any


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InternalMed_Harrison. and fibrosis (at the site or sites of cardiomyocyte death). In effect, the major therapies for AMI address these intermediate pathophenotypes (e.g., antithrombotics, statins) rather than any organ-specific disease-determining process. This paradigm would argue for a systems-based analysis that would first identify the intermediate pathophenotypes to which a person is predisposed, then determine how and when to intervene to attenuate that adverse predisposition, and finally limit the likelihood that a major organ-specific event will occur. Evidence for the validity of this approach is found in the work of Rzhetsky and colleagues, who reviewed 1.5 million patient records and 161 diseases and found that these disease phenotypes form a network of strong pairwise correlations. This result is consistent with the notion that underlying genetic predispositions to intermediate pathophenotypes form the predicate basis for conventionally defined end organ diseases.


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InternalMed_Harrison. Regardless of the specific nature of the systems pathobiologic approach used, these analyses will lead to a drastic revision of the way human disease is defined and treated, establishing the discipline of network medicine. This will be a lengthy and complicated process but ultimately will lead to better disease prevention and therapy and probably do so from an increasingly personalized perspective. The analysis of pathobiology from a systems-based perspective is likely to help define specific subsets of patients more likely to respond to particular interventions based on shared disease mechanisms. Although it is unlikely that the extreme of “individualized medicine” will ever be practical (or even desirable), complex diseases can be mechanistically subclassified and interventions may be tailored to those settings in which they are more likely to work.


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InternalMed_Harrison. G5,...,GnG1 G3 G2 G4 D5,...,DnD1 D3 D2 D4 I5 ... InI1 I3 I2 I4 E5 ... EnE1 E3 E2 E4 PS5 ... PSnPS1 PS3 PS2 PS4 P5 ... PnP1 P3 P2 P4 Primary disease genome Intermediate pathophenotype Pathophenome


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InternalMed_Harrison. HbSTGF˜HbC˜-ThalHbFImmuneresponseInflammationHemolyticanemiaAplasticanemiaStrokePainfulcrisisDisease-modifyinggenesIntermediatephenotypesPathophenotypeG6PDApoptosis/necrosisEnvironmentaldeterminantsHypoxiaDehydrationAcutechestsyndromeBoneinfarctThrombosisInfectiveagentFIGuRE 87e-3 A. Theoretical human disease network illustrating the relationships among genetic and environmental determinants of the pathophenotypes. Key: D, secondary disease genome or proteome; E, environmental determinants; G, primary disease genome or proteome; I, intermediate phenotype; PS, pathophysiologic states leading to P, pathophenotype. B. Example of this theoretical construct applied to sickle cell disease. Key: Red, primary molecular abnormality; gray, disease-modifying genes; yellow, intermediate phenotypes; green, environmental determinants; blue, pathophenotypes. (Reproduced with permission from J Loscalzo et al: Molec Syst Biol 3:124, 2007.)


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InternalMed_Harrison. Chapter 87e Network Medicine: Systems Biology in Health and Disease GNAS Developmental Ear, nose, throat Endocrine FIGuRE 87e-4 A. Human disease network. Each node corresponds to a specific disorder colored by class (22 classes, shown in the key to B). The size of each node is proportional to the number of genes contributing to the disorder. Edges between disorders in the same disorder class are colored with the same (lighter) color, and edges connecting different disorder classes are colored gray, with the thickness of the edge proportional to the number of genes shared by the disorders connected by it. B. Disease gene network. Each node is a single gene, and any two genes are connected if implicated in the same disorder. In this network map, the size of each node is proportional to the number of specific disorders in which the gene is implicated. (Reproduced with permission from KI Goh et al: Proc Natl Acad Sci USA 104:8685, 2007.)


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InternalMed_Harrison. FIGuRE 87e-5. The elements of the interactome. The interactome includes topologic modules (genes or gene products that are closely associated with one another through direct interactions), functional modules (genes or gene products that work together to define a pathway), and disease modules (genes or gene products that interact to yield a pathophenotype). (Reproduced with permission from AL Barabasi et al: Nat Rev Genet 12:56, 2011.) i. Interactome reconstruction iii. Disease module identification iv. Pathway identification v. Validation/prediction Potential sources: (i) OMIM (ii) GWAS ii. Disease gene (seed) identification Disease1 protein Disease2 protein Overlappingprotein Known disease2 protein Predicted disease2 protein Chapter 87e Network Medicine: Systems Biology in Health and Disease


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InternalMed_Harrison. Chapter 87e Network Medicine: Systems Biology in Health and Disease FIGuRE 87e-6. Approaches to identifying disease modules in molecular networks. A strategy for defining disease modules involves (i) reconstructing the interactome; (ii) ascertaining potential seed (disease) genes from the curated literature, the Online Mendelian Inheritance in Man (OMIM) database, or genomic analyses (genome-wide association studies [GWAS] or transcriptional profiling); (iii) identifying the disease module using different modeling or statistical approaches; (iv) identifying pathways and the role of disease genes or modules in those pathways; and (v) disease module validation and prediction. (Reproduced with permission from AL Barabasi et al: Nat Rev Genet 12:56, 2011.) http://vip.persianss.ir


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InternalMed_Harrison. Stem Cell Biology Minoru S. H. Ko Stem cell biology is a rapidly expanding field that explores the charac-teristics and possible clinical applications of a variety of stem cells that serve as the progenitors of more differentiated cell types. In addition to potential therapeutic applications (Chap. 90e), patient-derived 88 PART 4: Regenerative Medicine stem cells can also be used as disease models and as a means of testing drug efficacy. Stem cells and their niche are a major focus of medical research because they play central roles in tissue and organ homeostasis and repair, which are important aspects of aging and disease.


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InternalMed_Harrison. IDENTIFICATION, ISOLATION, AND DERIVATION OF STEM CELLS Resident Stem Cells The definition of stem cells remains elusive. Stem cells were originally postulated as unspecified or undifferentiated cells that provide a source of renewal of skin, intestine, and blood cells throughout life. These resident stem cells have been identified in a variety of organs (e.g., epithelia of the skin and digestive system, bone marrow, blood vessels, brain, skeletal muscle, liver, testis, and pancreas) based on their specific locations, morphology, and biochemical markers.


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InternalMed_Harrison. Isolated Stem Cells Unequivocal identification of stem cells requires their separation and purification, usually based on a combination of specific cell-surface markers. These isolated stem cells (e.g., hematopoietic stem [HS] cells) can be studied in detail and used in clinical applications, such as bone marrow transplantation (Chap. 89e). However, the lack of specific cell-surface markers for other types of stem cells has made it difficult to isolate them in large quantities. This challenge has been partially addressed in animal models by genetically marking different cell types with green-fluorescent protein driven by cell-specific promoters. Alternatively, putative stem cells have been isolated from a variety of tissues as side population (SP) cells using fluorescence-activated cell sorting after staining with the Hoechst 33342 dye.


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InternalMed_Harrison. Cultured Stem Cells It is desirable to culture and expand stem cells in vitro to obtain a sufficient quantity for analysis and potential therapeutic use. Although the derivation of stem cells in vitro has been a major obstacle in stem cell biology, the number and types of cultured stem cells have increased progressively (Table 88-1). Cultured stem cells derived from resident stem cells are often called adult stem cells or somatic stem cells to distinguish them from embryonic stem (ES) and embryonic germ (EG) cells. However, considering the existence of embryo-derived, tissue-specific stem cells (e.g., trophoblast stem [TS] cells) and the possible derivation of similar cells from an embryo/fetus (e.g., neural stem [NS] cells), it is more appropriate to use the term, tissue stem cells.


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InternalMed_Harrison. Successful derivation of cultured stem cells (both embryonic and tissue stem cells) often requires the identification of necessary growth factors and culture conditions, mimicking the microenvironment or niche of the resident stem cells. Recently, long-term maintenance of tissue stem cells in vitro is increasingly possible by growing them as three-dimensional (3D) organoids, which contain both stem cells and niche cells (Chap. 92e). For example, intestinal stem cells can now be cultured as “epithelial mini-guts” in the presence of R-spondin, epidermal growth factor (EGF), and noggin on Matrigel. Similarly, lung stem cells can be cultured as self-renewing “alveolospheres.” A growing list of cultured stem cells, although not comprehensive, is shown in Table 88-1. Please note that the establishment of cultured stem cells is often under dispute due to the difficulties in assessing the characteristics of these cells.


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InternalMed_Harrison. SELF-RENEWAL AND PROLIFERATION OF STEM CELLS Symmetric and Asymmetric Cell Division The most widely accepted stem cell definition is a cell with a unique capacity to produce unaltered daughter cells (self-renewal) and to generate specialized cell types (potency). Self-renewal can be achieved in two ways. Asymmetric cell division produces one daughter cell that is identical to the parental cell and one daughter cell that is different from the parental cell and is a progenitor or differentiated cell. Asymmetric cell division does not increase the number of stem cells. Symmetric cell division produces two Embryonic stem cells (ES, ESC) Blastocysts or immunosurgically isolated inner cell mass (ICM) from blastocysts Embryonic germ cells (EG, EGC) Primordial germ cells (PGCs) from embryos at E8.5–E12.5 (m); gonadal tissues from 5–11 week postfertilization embryo/fetus (h)


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InternalMed_Harrison. Embryonic germ cells (EG, EGC) Primordial germ cells (PGCs) from embryos at E8.5–E12.5 (m); gonadal tissues from 5–11 week postfertilization embryo/fetus (h) Trophoblast stem cells (TS, TSC) Trophectoderm of E3.5 blastocysts, extraembryonic ectoderm of E6.5 embryos, and chorionic ectoderm of E7.5 embryos (m) Embryonal carcinoma cells (EC) Teratocarcinoma—a type of cancer that develops in the testes and ovaries (m, h) Mesenchymal stem cells (MS, MSC) Bone marrow, muscle, adipose tissue, peripheral blood, and umbilical cord blood (m, h) Multipotent adult stem cells (MAPC) Bone marrow mononuclear cells (m, h); postnatal muscle and brain (m) Spermatogonial stem cells (SS, SSC) Newborn testis (m) Germline stem cells (GS, GSC) Neonatal testis (m) Multipotent adult germline stem cells Adult testis (m) (maGSC) Neural stem cells (NS, NSC) Fetal and adult brain (subventricular zone, ventricular zone, and hippo-campus) (m, h)


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InternalMed_Harrison. Neural stem cells (NS, NSC) Fetal and adult brain (subventricular zone, ventricular zone, and hippo-campus) (m, h) Unrestricted somatic stem cells Mononuclear fraction of cord blood (USSC) (h) Epistem cells (EpiSC) Early postimplantation epiblast (m) Induced pluripotent stem cells (iPS, Variety of terminally differentiated iPSC) cells and tissue stem cells (m, h) Lung stem cells Lung (m, h) Amniotic fluid-derived stem (AFS) Amniotic fluid (m, h) cells Umbilical cord blood stem cells Umbilical cord (h) Adipose stem cells (AST) Fat (m, h) Cardiac stem cells Heart (m, h) Renal stem cells Renal papilla (m, h) Crypt stem cells Intestine (m, h) Colon stem cells (CoSC) Colon (m, h) Hepatic stem cells Liver (m, h) Dental pulp stem cells (DPSC) Dental pulp (m, h) Hair follicle stem cells Hair (m, h) Abbreviations: h, human; m, mouse. identical daughter cells. For stem cells to proliferate in vitro, they must divide symmetrically.


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InternalMed_Harrison. Abbreviations: h, human; m, mouse. identical daughter cells. For stem cells to proliferate in vitro, they must divide symmetrically. Unlimited Expansion In Vitro Resident stem cells are often quiescent and divide infrequently. However, once the stem cells are successfully cultured in vitro, they often acquire the capacity to divide continuously and the ability to proliferate beyond the normal passage limit typical of primary cultured cells (sometimes called immortality). These features are primarily seen in ES cells but have also been demonstrated for tissue stem cells, such as NS cells and mesenchymal stem (MS) cells, thereby enhancing the potential of these cells for therapeutic use (Table 88-1).


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InternalMed_Harrison. Stability of Genotype and Phenotype The capacity to actively proliferate is often associated with the accumulation of chromosomal abnormalities and mutations. Mouse ES cells appear to be an exception to this rule and tend to maintain their euploid karyotype and genome integrity. By contrast, human ES cells appear to be more susceptible to mutations after long-term culture. However, it is also important to note that even euploid mouse ES cells can form teratomas when injected into immunosuppressed animals, raising concerns about the possible formation of tumors after transplanting actively dividing stem cells.


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InternalMed_Harrison. POTENCY AND DIFFERENTIATION OF STEM CELLS Developmental Potency The term potency is used to indicate a cell’s ability to differentiate into multiple specialized cell types. The current lack of knowledge about the molecular nature of potency requires the experimental manipulation of stem cells to demonstrate their potency. For example, in vivo testing can be done by injecting stem cells into mouse blastocysts or immunosuppressed adult mice and determining how many different cell types are formed from the injected cells. However, these in vivo assays are not applicable to human stem cells. In vitro testing can be performed by differentiating cells in various culture conditions to determine how many different cell types are formed from the cells. The formal test of self-renewal and potency is performed by demonstrating that a single cell possesses such abilities in vitro (clonality). Cultured stem cells are tentatively grouped according to their potency (Fig. 88-1). Only some examples


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InternalMed_Harrison. is performed by demonstrating that a single cell possesses such abilities in vitro (clonality). Cultured stem cells are tentatively grouped according to their potency (Fig. 88-1). Only some examples are shown, because many cultured stem cells, especially human cells, lack definitive information about their developmental potency.


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InternalMed_Harrison. From Totipotency to Unipotency Totipotent cells can form an entire organism autonomously. Only a fertilized egg (zygote) possesses this feature. Pluripotent cells (e.g., ES cells) can form almost all of the body’s cell lineages (endoderm, mesoderm, and ectoderm), including germ cells. Multipotent cells (e.g., HS cells) can form multiple cell lineages FIGURE 88-1 Potency and source developmental stage of cultured stem cells. For abbreviations of stem cells, see Table 88-1. Note that stem cells are often abbreviated with or without “cells,” e.g., ES cells or ESCs for embryonic stem cells. h, human; m, mouse.


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InternalMed_Harrison. but cannot form all of the body’s cell lineages. Oligopotent cells (e.g., NS cells) can form more than one cell lineage but are more restricted than multipotent cells. Oligopotent cells are sometimes called progenitor cells or precursor cells; however, these terms are often more strictly used to define partially differentiated or lineage-committed cells (e.g., myeloid progenitor cells) that can divide into different cell types but lack self-renewing capacity. Unipotent cells or monopotent cells (e.g., spermatogonial stem [SS] cells) can form a single differentiated cell lineage.


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InternalMed_Harrison. Nuclear Reprogramming Development naturally progresses from totipotent fertilized eggs to pluripotent epiblast cells to multipotent cells and, finally, to terminally differentiated cells. According to Waddington’s epigenetic landscape, this is analogous to a ball moving down a slope. The reversal of the terminally differentiated cells to totipotent or pluripotent cells (called nuclear reprogramming) can thus be seen as an uphill gradient. Nuclear reprogramming has been achieved using nuclear transplantation, or nuclear transfer (NT), procedures (often called “cloning”), where the nucleus of a differentiated cell is transferred into an enucleated oocyte. Although this is an error-prone procedure with a very low success rate, live animals have been produced using adult somatic cells as donors in sheep, mice, and other mammals. In mice, it has been demonstrated that ES cells derived from blastocysts made by somatic cell NT are indistinguishable from normal ES cells. NT can potentially be


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InternalMed_Harrison. in sheep, mice, and other mammals. In mice, it has been demonstrated that ES cells derived from blastocysts made by somatic cell NT are indistinguishable from normal ES cells. NT can potentially be used to produce patient-specific ES cells carrying a genome identical to that of the patient, although such strategies have not been pursued due to ethical issues and technical challenges. Recent success in generating human ES cells by NT has rekindled an interest in this area; however, the limited supply of human oocytes will still be a major problem for clinical applications of NT.


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InternalMed_Harrison. An alternative approach that has become a method of choice is the direct conversion of terminally differentiated cells into ES-like cells (called induced pluripotent stem [iPS] cells) by overexpressing a combination of key transcription factors (TFs). The original method was to infect mouse embryonic fibroblast cells with retrovirus vectors carrying four TFs [Pou5f1 (Oct4), Sox2, Klf4, and Myc] and to identify rare ES-like cells in culture. This approach was soon adapted to human cells, followed by a more refined procedure (e.g., the use of fewer TFs, different cell types, and different gene-delivery methods). Because a clinical trial using iPS cells is imminent, the safety of iPS-based therapy is a major concern and a variety of measures are being taken to ensure the safety. For example, it has now become a standard to use footprint-free methods such as an episomal vector, Sendai virus vector, and synthetic mRNAs to deliver reprogramming factors into cells, resulting in the


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InternalMed_Harrison. example, it has now become a standard to use footprint-free methods such as an episomal vector, Sendai virus vector, and synthetic mRNAs to deliver reprogramming factors into cells, resulting in the production of patient-specific iPS cells with minimal alteration of their genetic makeup. In addition to cell replacement therapy, disease-specific iPS cells are expected to play a role in modeling human disease in vitro and in screening drugs for personalized medicine.


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InternalMed_Harrison. It has also become possible to convert one type of terminally differentiated cell (e.g., fibroblast cell) into another type of terminally differentiated cell (e.g., cardiac muscle, neuron, or hepatocyte) by overexpressing specific sets of TFs (called direct reprogramming). Direct reprogramming can bypass the step of making iPS cells, possibly providing the safer route to desired cell types for therapy; however, the technology is currently limited by its low efficiency.


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InternalMed_Harrison. Stem Cell Plasticity, Transdifferentiation, and Facultative Stem Cells The prevailing paradigm in developmental biology is that once cells are differentiated, their phenotypes are stable. However, more recent studies show that tissue stem cells, which have traditionally been thought to be lineage-committed multipotent cells, possess the capacity to differentiate into cell types outside their lineage restrictions (called transdifferentiation). For example, HS cells may be converted into neurons as well as germ cells. This feature may provide a means to use tissue stem cells derived directly from a patient for therapeutic purposes, thereby eliminating the need to use embryonic stem cells or elaborate procedures such as nuclear reprogramming of a patient’s somatic cells. However, more strict criteria and rigorous validation are required to establish tissue stem cell plasticity. For example, observations of transdifferentiation may reflect cell fusion, contamination with progenitor cells


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InternalMed_Harrison. criteria and rigorous validation are required to establish tissue stem cell plasticity. For example, observations of transdifferentiation may reflect cell fusion, contamination with progenitor cells from other cell lineages, or persistence of pluripotent embryonic cells in adult organs. Therefore, the assignment of potency to each cultured stem cell in Fig. 88-1 should be considered with caution. Whether transdifferentiation exists and can be used for therapeutic purposes remains to be determined conclusively. A similar, but distinct, concept is the facultative stem cell, which is defined as a unipotent cell or a terminally differentiated cell that can function as a stem cell upon tissue injury. The presence of such cells has been proposed for some organs such as liver, intestine, pancreas, and testis, but is still debated.


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InternalMed_Harrison. Directed Differentiation of Stem Cells Pluripotent stem cells (e.g., ES and iPS cells) can differentiate into multiple cell types, but in culture, they normally differentiate into heterogeneous cell populations in a stochastic manner. However, for therapeutic uses, it is desirable to direct stem cells into specific cell types (e.g., insulin-secreting beta cells). This is an active area of stem cell research, and protocols are being developed to achieve this goal. In any of these directed cell differentiation systems, the cell phenotype must be evaluated critically. Alternatively, the heterogeneity of the cell population derived from pluripotent stem cells can be actively exploited, as different types of cells interact with each other in culture and further enhance their own differentiation. In some instances, e.g., optic cup, self-organizing tissue morphogenesis has been demonstrated in 3D culture.


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InternalMed_Harrison. MOLECULAR CHARACTERIZATION OF STEM CELLS Genomics and Proteomics In addition to standard molecular biological approaches, high-throughput genomics and proteomics have been extensively applied to the analysis of stem cells. For example, DNA microarray analyses have revealed the expression levels of essentially all genes and identified specific markers for some stem cells. Chromatin immunoprecipitation coupled with next-generation sequencing technologies, capable of producing billions of sequence reads in a single run, has revealed chromatin modifications (“epigenetic marks”) relevant to stem cell properties. Similarly, the protein profiles of stem cells have been assessed by using mass spectrometry. These methods are beginning to provide a novel means to characterize and classify various stem cells and the molecular mechanisms that give them their unique characteristics.