![[Feedback]](/icons/banner/feedbackACT.gif){kind=icon}
![[For Subscribers]](/icons/banner/subscriberACT.gif){kind=icon}
![[Archive]](/icons/banner/archiveACT.gif){kind=icon}
![[Search]](/icons/banner/searchACT.gif){kind=icon}
![[Contents]](/icons/banner/tocACT.gif){kind=icon}
|
|
|
|
|
||
Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, Baltimore, MD 21201
2To whom correspondence should be addressed. E-mail: jmorris{at}epi.umaryland.edu.
 |
ABSTRACT |
|---|
 TOP ABSTRACT LITERATURE CITED |
|---|
KEY WORDS: • intestinal microbiota • molecular tools • diet • human disease
Bacteria have been known to be closely associated with mammals since the development of optical tools allowed for the visualization of such microbes. Even before bacteria could be viewed by microscopy, infectious small particles (animalcules) had been suspected to cause various transmissible human diseases (1). Modern microbiology has established the close associations of bacteria with mammals not only as a cause of disease, but also as part of an essential colonizing microflora (2,3).
Commensal bacterial communities are closely associated with the human skin, oral cavity, gastrointestinal tract and the female genital tract. The colon, in particular, is the home for a complex consortium of microorganisms (primarily bacteria, but also fungi and protozoa) that is critical for normal health. The actual number of species that may be present is controversial; it has been estimated that >500 species coexist in the human colon, although statistical extrapolations from the 16S rDNA sequencing of cloned amplicons derived from human fecal community DNA from one patient suggest that there are <150 operational taxonomic units (defined as differing in 16S rDNA sequence by < 2%) (4,5). Future studies that utilize a combination of conventional and molecular microflora analysis tools will help to better define the complexity of the human microbiota. It has further been estimated that some 40 species make up 
99% of all isolates, with the Bacteroides-Prevotella group (a Gram-negative anaerobe) and Clostridium species (Gram-positive anaerobes) predominating (3,6,7).
In the colon of healthy humans, anaerobic species outnumber aerobic ones by at least 10-fold, with the proportion of anaerobes to aerobes having been used as a measure for "normal" flora. The composition of the microflora changes throughout the intestinal tract, with the highest microbial activity observed in the proximal colon (2,6). The composition of the microflora appears to be affected by changes in substrate availability, pH and reduction potential. The total number of microbes in the gastrointestinal tract seems to be similar in different human populations and has been estimated to be an order of magnitude higher than the number of eucaryotic cells in the entire human body (8).
Host-associated bacteria with their metabolic contributions to host physiology have clear trophic functions and play a role in protecting the host against invasion by pathogenic species. Bacterial fermentation products such as short chain fatty acids can be nutrients as well as growth signals for the intestinal epithelium, an example being butyrate with its pro-differentiation, anti-proliferation and anti-angiogenic effects on colonocytes (9–11). Various bioactive molecules such as carcinogenic xenobiotics, dietary phytoestrogens, and primary bile acids can be transformed by commensal bacteria (12–14). The microflora facilitates the excretion of various toxic substances and the exclusion of pathogenic microorganisms from the human host. Furthermore, the normal flora has been shown to stimulate immune function through Peyer’s patches and other gut-associated lymphoid tissue (GALT),3 which are distributed throughout the gastrointestinal tract (15). The commensal microflora is involved in the regulation of gastrointestinal immune tolerance, disturbances of which can contribute to diseases such as Crohn’s disease and ulcerative colitis (16,17). Specific host-microbe interactions have been reported that can regulate production and excretion of selective sugars into the intestinal lumen (18,19). This observation suggests that microbes have evolved synergistic mechanisms to influence the colonic environment for their own benefit, and potentially that of the host, by affecting epithelial host cell gene expression. Although interest in the role of the commensal microflora has been renewed by the development and refinement of molecular analysis tools (reviewed by R. Gaskins et al. in an accompanying article in this issue) including the availability of completed genome sequences (20–22), our understanding of the dynamics and physiologic functions of the microflora is still in its infancy. In this paper we review recent advances in understanding the associations between diet, microflora, and health, in the context of the increasing availability of molecular tools.
The molecular age of microflora analysis
Traditionally, the stool flora has been analyzed by microbiological culture techniques. However, this approach is rather laborious, time consuming and often inaccurate. It is also limited in scope, as a majority of the bacterial species present in feces are not culturable using standard microbiologic techniques (19,23). Even among those that are culturable, species identification by traditional identification methods is often difficult, if not impossible; only a limited number of species have been fully characterized, and biochemical identification systems may have minimal utility in differentiating species (2,3).
The first widely used molecular technique in microbial systematics, which still required culturing of the respective bacteria, was total genomic DNA hybridization. This approach, which utilizes whole genomes rather than small genomic regions to determine the degree of similarity between two microbes, formed the basis for molecular microbial phylogeny before the advent of the 16S rDNA revolution. Molecular tools based on 16S rDNA sequence similarities such as fluorescent in-situ hybridization (FISH), denaturing gradient gel electrophoresis (DGGE), quantitative dot blot hybridization, restriction fragment length polymorphism, and large scale 16S rDNA sequencing have helped to overcome limitations of conventional microbiological plating methods in studying the fecal microflora composition (2,24); they are reviewed in detail elsewhere in this issue. Microchips that would allow for more efficient identification of bacterial species present in complex communities are currently under development in various laboratories. While the feasibility of the microchip approach has been established, currently available chips are still limited in scope. Microchips specifically designed to analyze the human fecal microflora should make it possible to extend studies of the associations between diet, microflora, and health to large prospective cohort studies, a necessary next step in dealing with these questions.
In limited studies, molecular tools have been applied to study the development of the infant microflora (25,26) and changes in the human microflora during aging, with the suggestion that complexity increases with age (with a corresponding decrease in the number of Bifidobacteria) (6,27). These tools have also been used to evaluate the effects of pre- and probiotics on the human microflora composition (15,28) and the effects of dietary interventions on the intestinal microflora in various animal models, as outlined below (29,30). These studies have also underscored the degree of variability inherent to these types of complex systems (and assay systems). For example, a microflora study based on FISH analyses has shown a large degree of variability among subjects and in individuals over time (31). Although some of this observed variation is likely due to differences in environmental factors such as diet, other factors, including host genetics and the potential contribution of chance, cannot be neglected. Establishment and maintenance of the commensal microflora is a complex and multi-factorial process that we do not fully understand. The sequence in which bacteria settle a niche in the colon, due to chance encounters, nutrient supply, and immune surveillance, may well influence the ability of other bacteria to establish residence.
Molecular studies have highlighted the diversity of the flora within individuals. In this context, it is somewhat surprising that sequencing large numbers of16S rDNA clones derived from fecal microflora communities has not resulted in large numbers of identical or highly similar sequences, which might have been expected from prior work indicating the predominance of a few genera in the microflora (5,7,32). Wilson and Blitchington undertook direct amplification and partial sequencing of cloned 16S genes from community DNA extracted from a human fecal sample. Fifty isolated clones had 27 distinct sequences and gave an estimated 59% coverage of cloned 16S rDNAs (32). More recently, Suau et al. examined 284 16S rDNA sequences from human intestinal microbiota and found 82 molecular species from three dominant groups: Clostridia coccoides-like, C. leptum-like, and Bacteroides (5). However, many different rather than a few dominant species were identified within these three groups. Similar observations were made in pigs, where 16S rDNA sequences analysis detected 375 different phylotypes in 24 pigs (33) and chaperonine-60 analysis detected 398 different nucleotide sequences encoding 280 different peptide sequences (34).
These observations raise the possibility that the intestinal microflora contains large numbers of different species, each of which is present only in low numbers. Bias introduced through PCR or subcloning might affect such analyses (35); the extent of such potential distortions has not been thoroughly investigated. Future human microflora studies based on large numbers of cloned 16S rDNA sequences might well change current concepts of intestinal colonization and microflora composition. It should be emphasized that sequencing studies of the human microflora have not reached the point of saturation. It may be necessary to sequence well over a thousand clones per sample before reaching a point at which additional sequences will be unlikely to yield more unique sequences (unpublished results, C. Stine). A high proportion of sequences discovered in sequencing studies have not previously been described. Both of the human studies summarized above found that only a quarter of the sequences corresponded to known sequences even when allowing for a 2% divergence between the observed and data base sequences.
Due to relative ease of stool collection most of the intestinal microflora studies have been performed under the assumption that feces contain a representative sample of the prevalent intestinal microflora. Although some studies have shown clear differences between the fecal microflora composition and the kinds of bacteria that are present at other anatomical sites, including bacteria in the cecum (36) and those associated with the mucosa (37), differences in the human microflora at various anatomical sites are not well documented. It can be assumed that while the proportions and activities of the microflora change with passage through the intestinal tract, most viable as well as nonviable commensal intestinal bacteria will still be detectable in feces with molecular methods. Until new nanotechnologies allowing for the convenient sampling of microflora throughout the intestinal tract become more widely available, feces remain the only realistic sample in large noninvasive studies. Before large human studies can be designed it needs to be unequivocally established that analyzing microflora composition and activities in feces is representative of important intestinal parameters.
Although the 16S rDNA based technologies continue to undergo refinement, it might be timely to develop standardized protocols for the analysis of the intestinal microflora, which would facilitate an improved comparison of results across studies. Such an effort could lead to the establishment of a single database that contains the fecal bacterial profiles from subjects across various studies. Given their expense, studies to date have generally involved small numbers of patients (or one patient); establishment of a common database would facilitate comparison of such data, allowing for a better understanding of the complexity and the variation of the human intestinal microbiota.
Effects of diet on microflora composition
There have been several studies suggesting that each individual harbors his or her own distinctive pattern of intestinal microflora composition. This pattern tends to remain constant across time, although there may be some increase in species diversity with age (27,38). While studies are limited, it appears that overall dietary patterns (as seen among persons living in different geographic areas) and intake of various nutrients can influence general patterns of fecal microflora (39–41). At the same time, and in keeping with prior comments about the variability of results, in subjects in a feeding study the same diet may have very different effects on the microflora, possibly due to differential effects of the diet on the individual’s underlying microflora composition, and/or underlying genetic differences (Mai et al., this issue).
Most molecular studies of the associations between nutrients and microflora composition have been done with supplements that supply either viable bacteria (probiotics), oligosaccharides that can selectively enhance the growth of "beneficial" bacteria (prebiotics), or a combination of both (synbiotics). The effectiveness of these supplements in modulating the intestinal microflora toward a composition with increased proportions of bacteria that are thought to be beneficial, such as Bifidobacteria and Lactic Acid Bacteria (LAB), is well-established (15,28,42). Other studies have focused on differences in the fecal microflora of neonates that are fed either breast milk or formula (25,26). These studies have shown that feeding breast milk results in the development of an intestinal microflora that has increased proportions of Bifidobacteria.
It is important to note that labeling nonpathogenic commensal bacteria as either beneficial or detrimental remains highly speculative. For instance, although it is widely assumed that Bifidobacteria and LAB are beneficial whereas high numbers of Clostridia and Bacteroides are detrimental, labeling them as such is not necessarily supported by rigorous data. In fact, one study showed that although LAB were inversely associated with colorectal carcinogenesis (CRC), a positive association with CRC was observed not only for Bacteroides but also for Bifidobacterium species (38). In vitro studies that investigate the effects of specific bacteria on cancer cell lines, which already have undergone a variety of genetic alterations and which do not resemble the physiologic and immunologic conditions that are found in the colon, and animal studies that evaluate the effects of microflora changes in either germ free, rodent-flora or human-flora associated rodents should be interpreted very carefully. The complexity and the dynamics of the human microflora, which we know very little about, and its potential species or even strain specific interactions with the human host including its immune system cannot be effectively studied in any simplified model system. Thus, claims of associations between specific commensal bacterial species or strains and human health will have to be established in human feeding/intervention studies or large epidemiologic studies. The available molecular tools should now allow for such studies. Model systems should be continued to be utilized a) to establish if and how intestinal microflora composition and activity can be modulated by complex diets, and b) to strengthen the hypothesis that specific commensal bacteria or microflora profiles are associated with specific diseases including carcinogenesis.
Unfortunately, studies of specific interactions between diets that differ in macronutrient content and microflora composition have not yet been carefully investigated with 16S rDNA based molecular tools. Early ecological studies have suggested that fecal microflora differences in populations with varying dietary habits contribute to the observed differences in health in these groups. Studies based on conventional culturing techniques have indicated that the protein and fat content of the diet as well as the nature of the carbohydrates (simple sugars vs. complex carbohydrates) does affect microflora composition and activity (41,43,44). Animal studies support the hypothesis that the intestinal microflora can be modified by diet and antibiotic administration in mice and chicken (29,45). However, as mentioned above, studies that evaluate effects of dietary interventions on the intestinal microflora often use different methods and thus have to be interpreted with caution. For instance, food restriction, arguably one of the most effective dietary interventions, has been shown in one study to have little effect on the microflora of rats as measured by conventional anaerobic culture, cellular fatty acid profile and PCR (46). In contrast, we have observed that food restriction and diet composition both strongly affect the microflora composition as judged by DGGE (47). Standardized 16S rDNA based molecular tools should now be used, preferably in combination with conventional methods, to study in depth in both human and animal models the natural variation in the microflora and interactions between diet and the composition and activities of the intestinal microflora.
Intestinal microflora composition and health
At the beginning of the last century Metchnikoff suggested that the use of live bacteria in fermented milk products such as yogurt could increase longevity and improve health by detoxifying putrefactive substances (48). In the more recent past interest in the potential of improving human health through modifications of the intestinal microflora has reemerged and various dairy products that are commercially available claim such effects. It has, however, been difficult to establish the existence of associations between specific microbes and health. Studies that attempt to associate complex diets with changes in the microflora and disease are virtually nonexistent.
The recent literature on the efficacy of probiotic interventions supports the hypothesis that changes in the microflora induced by the consumption of probiotics can reduce the frequency and severity of diarrhea, as well as atopic disease in infants (49–52). Crohn’s disease, inflammatory bowel disease, and gastrointestinal cancers are thought to be associated with the microflora composition and recent data supports such association (23,53–55). Although epidemiologic studies do not support an inverse association between intake of fermented milk products and colorectal cancer (56,57), these studies are limited in scope because they neither differentiate between viable and nonviable products nor between the specificity of the consumed bacterial strains.
Many potential mechanisms have been suggested to mediate the proposed associations between microflora and human health (58), but only a few of them have been well established. The commensal microflora might participate in a) excluding pathogenic organisms from colonizing the gut through strengthening the barrier function or competing for attachment sites; b) interacting with the intestinal immune system, contributing to the regulation of immune function including tolerance; c) producing either beneficial or harmful fermentation end products (butyrate, acetaldehyde) that might change intestinal pH; d) facilitating the metabolic conversion and uptake of beneficial dietary components (phytoestrogens, vitamins); e) transforming and/or excreting toxic substances (bile acids, nitroseamines, heterocyclic amines); and f) generating fecal bulk that might decrease transit time and lower exposure of the intestinal lumen to toxic substances. More specific interactions have recently emerged, including the molecular communication between B. thetaiotaomicron and the intestinal epithelium (19) and the proposed associations between enterotoxic B. fragilis (increased risk) (59,60) or enterotoxigenic E.coli (decreased risk) (61) and colorectal carcinogenesis.
Diet, microflora and colon cancer
Colorectal cancer is one of the four leading carcinomas in the United States today; NCI/SEER estimates are that 147,500 new patients with this disease will be diagnosed with this disease in 2003, with 57,100 deaths (62). While a portion (perhaps as much as 35%) of the predisposition to developing colon cancer is attributable to heredity, the majority of risk appears to come from nonhereditary environmental factors. Colon cancer is much less common in the underdeveloped countries/regions of Africa, Asia, and South or Central America than in developed Western societies [age standardized incidence of 9.91 vs. 37.30 cases/100,0000 population/y (IARC, Globocan)], consistent with the hypothesis that there are lifestyle or other factors within these societies that increase the risk of CRC (63). The importance of environmental factors is further supported by the observation that risk increases among low-risk population groups after movement to developed countries (and, presumably, assumption of the habits of these counties); for example, in one study of Chinese men, rates of colorectal cancer increased as much as twofold after migration from Shanghai to Los Angeles or Hawaii (63).
The possible role of diet as a risk factor for colon cancer has been examined in a number of epidemiologic studies. Early epidemiological observations suggested that diet could explain up to 90% of colorectal cancer risk (64). Although this level of involvement has not been supported by subsequent research, there remains a strong consensus that diet is an important component of the total risk profile. Several diet components consistently emerge from these studies, including total fat or saturated fatty acids and red meat as causal (with red meat having the greatest potential impact) and fruits and vegetables and, possibly, fiber, as protective (63,65–67). However, the evidence for many of these food groups does not reach the level of being conclusive (65).
In one study of associations between microflora composition and colorectal carcinogenesis (initiated in 1971 but not completed until 1995 because of technical difficulties in characterizing stool microflora), stool samples from rural South Africans were compared with those from rural Japanese (both groups consuming a "native" diet), and three groups eating a western-style diet, including Japanese-Hawaiians, whites from Hawaii and the continental U.S., and patients with a history of recent polyp removal (38). While each subject had his or her own unique pattern, the general fecal microflora pattern seen in the rural Japanese was distinctive from that of the other groups, as was that of the rural South Africans; composition of microflora was similar among the group with polyps and the Japanese-Hawaiians (with increased concentrations of Bacteriodes and Bifidobacterium species), while whites had patterns somewhere between these "high risk" persons and the rural "low risk" groups. At the species level, 13 species were significantly associated with a high risk of colon cancer and the western diet, while 6 species were associated with a low risk and the native diets. The numbers in the study were relatively small (total n = 88 for all groups), and more traditional microbiologic techniques were used for characterization of fecal microflora. Nonetheless, these data support the hypothesis that patterns of fecal microflora differ among groups from different geographic areas, who are consuming different types of diets, and who might be expected to have different cancer risks.
Some animal studies support the hypothesis that changes in the microflora contribute to intestinal carcinogenesis. In contrast, Dove et al. have argued that microflora might not play a role in intestinal carcinogenesis in APCMin mice, because the frequency of intestinal polyps was not different in germfree mice when compared with controls (68). However, their study does not exclude the possibility that specific bacterial strains might have either beneficial or detrimental effects on carcinogenesis in this cancer model. In fact, Schauer et al. have reported that inoculation of APCMin mice with Citrobacter rodentii increases intestinal polyp frequency (69).
Utilization of molecular tools in future studies
The scope of studies of the associations between microflora and human health has so far been limited to observational studies, controlled short term feeding studies and small-scale intervention studies. Although these studies have contributed significantly to our understanding of the human intestinal microflora, we are still lacking a comprehensive understanding of the strength of the associations between diet and microflora and the degree of variation within and among individuals.
Animal studies, which have the advantage of being well controlled for environmental and genetic factors, should be designed to evaluate microflora stability and the effects of dietary interventions on microflora composition and disease. Various existing models would allow for such studies with IBD or markers of intestinal carcinogenesis as the relevant end points. Although details from such studies will not be directly applicable to humans, such studies could strengthen the hypothesis that the effect of diet on health is modulated through effects on the microflora. Due to important differences in intestinal anatomy and physiology as well as in immune surveillance between humans and rodents, it is questionable that associating rodents with a human fecal microflora would be more informative than observing changes in the normal rodent microflora.
Molecular tools have the potential for allowing analysis of fecal samples from a large number of subjects. These tools need to be validated and standardized and should then be utilized to build a database of the human intestinal microbiota, which will form the basis for determining the degree to which the microflora can be influenced by dietary changes. A concerted, multidisciplinary effort, incorporating modern molecular tools for the microflora analysis in the setting of well-designed prospective studies, is needed to advance our knowledge of the complex interactions between host and microflora to the point that we can design effective dietary interventions. Ultimately, this should lead to clinical intervention studies to determine if diet-induced microflora changes can reduce the risk of major gastrointestinal diseases such as Crohn’s disease or colorectal cancer.
|
FOOTNOTES |
|---|
3 Abbreviations used: CRC, colorectal carcinogenesis; DGGE, denaturing gradient gel electrophoresis; FISH, fluorescent in-situ hybridization; GALT, gut-associated lymphoid tissue; LAB, Lactic Acid Bacteria.
|
LITERATURE CITED |
|---|
|
TOPABSTRACTLITERATURE CITED |
|---|
1. Lederberg, J. (2000) Infectious history. Science 288:287-293.
2. Tannock, G. W. (1999) Analysis of the intestinal microflora: a renaissance. Antonie Leeuwenhoek 76:265-278.
3. Tannock, G. W. (2002) Molecular methods for exploring the intestinal ecosystem. Br. J. Nutr. 87(Suppl 2):S199-S201.
4. Hughes, J. B., Hellmann, J. J., Ricketts, T. H. & Bohannan, B. J. (2001) Counting the uncountable: statistical approaches to estimating microbial diversity. Appl. Environ. Microbiol. 67:4399-4406.
5. Suau, A., Bonnet, R., Sutren, M., Godon, J.-J., Gibson, G. R., Collins, M. D. & Dore, J. (1999) Direct analysis of genes encoding 16S rRNA from complex communities reveals many novel molecular species within the human gut. Appl. Environ. Microbiol. 65:4799-4807.
6. Macfarlane, G. T. & Macfarlane, S. (1997) Human colonic microbiota: ecology, physiology and metabolic potential of intestinal bacteria. Scand. J. Gastroenterol. 222(Suppl.):3-9.
7. Hold, G. L., Pryde, S. E., Russell, V. J., Furrie, E. & Flint, H. J. (2002) Assessment of microbial diversity in human colonic samples by 16S rDNA sequence analysis. Fems Microbiol. Ecol. 39:33-39.
8. Rabiu, B. A. & Gibson, G. R. (2002) Carbohydrates: a limit on bacterial diversity within the colon. Biol. Rev. Camb. Philos. Soc. 77:443-453.[Medline]
9. Pryde, S. E., Duncan, S. H., Hold, G. L., Stewart, C. S. & Flint, H. J. (2002) The microbiology of butyrate formation in the human colon. FEMS Microbiol. Lett. 217:133-139.[Medline]
10. Avivi-Green, C., Polak-Charcon, S., Madar, Z. & Schwartz, B. (2000) Apoptosis cascade proteins are regulated in vivo by high intracolonic butyrate concentration: correlation with colon cancer inhibition. Oncol. Res. 12:83-95.[Medline]
11. Zgouras, D., Wachtershauser, A., Frings, D. & Stein, J. (2003) Butyrate impairs intestinal tumor cell-induced angiogenesis by inhibiting HIF-1alpha nuclear translocation. Biochem. Biophys. Res. Commun. 300:832-838.[Medline]
12. Orrhage, K. M., Annas, A., Nord, C. E., Brittebo, E. B. & Rafter, J. J. (2002) Effects of lactic acid bacteria on the uptake and distribution of the food mutagen Trp-P-2 in mice. Scand. J. Gastroenterol. 37:215-221.[Medline]
13. Blair, R. M., Appt, S. E., Franke, A. A. & Clarkson, T. B. (2003) Treatment with antibiotics reduces plasma equol concentration in cynomolgus monkeys (Macaca fascicularis). J. Nutr. 133:2262-2267.
14. Debruyne, P. R., Bruyneel, E. A., Li, X., Zimber, A., Gespach, C. & Mareel, M. M. (2001) The role of bile acids in carcinogenesis. Mutat. Res. 480–481:359-369.
15. Steer, T., Carpenter, H., Tuohy, K. & Gibson, G. R. (2000) Perspectives on the role of the human gut microbiota and its modulation by pro- and prebiotics. Nutr. Res. Rev. 13:229-254.[Medline]
16. Farrell, R. J. & LaMont, J. T. (2002) Microbial factors in inflammatory bowel disease. Gastroenterol. Clin. North Am. 31:41-62.[Medline]
17. Perdigon, G., Maldonado, G. C., Valdez, J. C. & Medici, M. (2002) Interaction of lactic acid bacteria with the gut immune system. Eur. J. Clin. Nutr. 56(Suppl 4):S21-S26.
18. Hooper, L. V., Wong, M. H., Thelin, A., Hansson, L., Falk, P. G. & Gordon, J. I. (2001) Molecular analysis of commensal host-microbial relationships in the intestine. Science 291:881-884.
19. Hooper, L. V., Midtvedt, T. & Gordon, J. I. (2002) How host-microbial interactions shape the nutrient environment of the mammalian intestine. Annu. Rev. Nutr. 22:283-307.[Medline]
20. Schell, M. A., Karmirantzou, M., Snel, B., Vilanova, D., Berger, B., Pessi, G., Zwahlen, M. C., Desiere, F. & Bork, P., et al (2002) The genome sequence of Bifidobacterium longum reflects its adaptation to the human gastrointestinal tract. Proc. Natl. Acad. Sci. U.S.A. 99:14422-14427.
21. Xu, J., Bjursell, M. K., Himrod, J., Deng, S., Carmichael, L. K., Chiang, H. C., Hooper, L. V. & Gordon, J. I. (2003) A genomic view of the human-Bacteroides thetaiotaomicron symbiosis. Science 299:2074-2076.
22. Paulsen, I. T., Banerjei, L., Myers, G. S., Nelson, K. E., Seshadri, R., Read, T. D., Fouts, D. E., Eisen, J. A. & Gill, S. R., et al (2003) Role of mobile DNA in the evolution of vancomycin-resistant Enterococcus faecalis. Science 299:2071-2074.
23. Seksik, P., Rigottier-Gois, L., Gramet, G., Sutren, M., Pochart, P., Marteau, P., Jian, R. & Dore, J. (2003) Alterations of the dominant faecal bacterial groups in patients with Crohn’s disease of the colon. Gut 52:237-242.
24. Vaughan, E. E., Schut, F, Heilig, H. G., Zoetendal, E. G., De Vos, W. M. & Akkermans, A. D. (2000) A molecular view of the intestinal ecosystem. Curr. Issues Intest. Microbiol. 1:1-12.[Medline]
25. Mountzouris, K. C., McCartney, A. L. & Gibson, G. R. (2002) Intestinal microflora of human infants and current trends for its nutritional modulation. Br. J. Nutr. 87:405-420.[Medline]
26. Harmsen, H. J., Wildeboer-Veloo, A. C., Raangs, G. C., Wagendorp, A. A., Klijn, N., Bindels, J. G. & Welling, G. W. (2000) Analysis of intestinal flora development in breast-fed and formula-fed infants by using molecular identification and detection methods. J. Pediatr. Gastroenterol. Nutr. 30:61-67.[Medline]
27. Blaut, M., Collins, M. D., Welling, G. W., Dore, J., van Loo, J. & de Vos, W. (2002) Molecular biological methods for studying the gut microbiota: the EU human gut flora project. Br. J. Nutr. 87(Suppl 2):S203-S211.
28. Kruse, H. P., Kleessen, B. & Blaut, M. (1999) Effects of inulin on faecal bifidobacteria in human subjects. Br. J. Nutr. 82:375-382.[Medline]
29. McCracken, V. J., Simpson, J. M., Mackie, R. I. & Gaskins, H. R. (2001) Molecular ecological analysis of dietary and antibiotic-induced alterations of the mouse intestinal microbiota. J. Nutr. 131:1862-1870.
30. Tajima, K., Aminov, R. I., Nagamine, T., Matsui, H., Nakamura, M. & Benno, Y. (2001) Diet-dependent shifts in the bacterial population of the rumen revealed with real-time PCR. Appl. Environ. Microbiol. 67:2766-2774.
31. Franks, A. H., Harmsen, H. J., Raangs, G. C., Jansen, G. J., Schut, F. & Welling, G. W. (1998) Variations of bacterial populations in human feces measured by fluorescent in situ hybridization with group-specific 16S rRNA-targeted oligonucleotide probes. Appl. Environ. Microbiol. 64:3336-3345.
32. Wilson, K. H. & Blitchington, R. B. (1996) Human colonic biota studied by ribosomal DNA sequence analysis. Appl. Environ. Microbiol. 62:2273-2278.
33. Leser, T. D., Amenuvor, J. Z., Jensen, T. K., Lindecrona, R. H., Boye, M. & Moller, K. (2002) Culture-independent analysis of gut bacteria: the pig gastrointestinal tract microbiota revisited. Appl. Environ. Microbiol. 68:673-690.
34. Hill, J. E., Seipp, R. P., Betts, M., Hawkins, L., Van Kessel, A. G., Crosby, W. L. & Hemmingsen, S. M. (2002) Extensive profiling of a complex microbial community by high-throughput sequencing. Appl. Environ. Microbiol. 68:3055-3066.
35. von Wintzingerode, F., Gobel, U. B. & Stackebrandt, E. (1997) Determination of microbial diversity in environmental samples: pitfalls of PCR-based rRNA analysis. FEMS Microbiol. Rev. 21:213-229.[Medline]
36. Marteau, P., Pochart, P., Dore, J., Bera-Maillet, C., Bernalier, A. & Corthier, G. (2001) Comparative study of bacterial groups within the human cecal and fecal microbiota. Appl. Environ. Microbiol. 67:4939-4942.
37. Zoetendal, E. G., von Wright, A., Vilpponen-Salmela, T., Ben Amor, K., Akkermans, A. D. & De Vos, W. M. (2002) Mucosa-associated bacteria in the human gastrointestinal tract are uniformly distributed along the colon and differ from the community recovered from feces. Appl. Environ. Microbiol. 68:3401-3407.
38. Moore, W. E. & Moore, L. H. (1995) Intestinal floras of populations that have a high risk of colon cancer. Appl. Environ. Microbiol. 61:3202-3207.
39. Finegold, S. M., Attebery, H. R. & Sutter, V. L. (1974) Effect of diet on human fecal flora: comparison of Japanese and American diets. Am. J. Clin. Nutr. 27:1456-1469.[Medline]
40. Hentges, D. J. (1980) Does diet influence human fecal microflora composition?. Nutr. Rev. 38:329-336.[Medline]
41. Hill, M. J. (1981) Diet and the human intestinal bacterial flora. Cancer Res 41:3778-3780.
42. Blaut, M. (2002) Relationship of prebiotics and food to intestinal microflora. Eur. J. Nutr. 41(Suppl 1):I11-I16.
43. Hill, M. J. (1998) Composition and control of ileal contents. Eur. J. Cancer Prev. 7(Suppl 2):S75-S78.
44. Goldin, B., Dwyer, J., Gorbach, S. L., Gordon, W. & Swenson, L. (1978) Influence of diet and age on fecal bacterial enzymes. Am. J. Clin. Nutr. 31:S136-S140.[Abstract]
45. Knarreborg, A., Simon, M. A., Engberg, R. M., Jensen, B. B. & Tannock, G. W. (2002) Effects of dietary fat source and subtherapeutic levels of antibiotic on the bacterial community in the ileum of broiler chickens at various ages. Appl. Environ. Microbiol. 68:5918-5924.
46. Henderson, A. L., Cao, W. W., Wang, R. F., Lu, M. H. & Cerniglia, C. E. (1998) The effect of food restriction on the composition of intestinal microflora in rats. Exp. Gerontol. 33:239-247.[Medline]
47. Mai, V., Colbert, L., Berrigan, D., Lavigne, J., Pfeiffer, R., Perkins, S. N., Srinivas, P., Lanza, E. & Schatzkin, A., et al (2002) Effects of calorie restriction and diet composition on intestinal carcinogenesis in ApcMin (Min) mice. Cancer Epidemiol. Biomark. Prev. 11:1184S.
48. Metchnikoff, E. (1907) The prolongation of life 1907 Heinemann London, UK.
49. Saarela, M., Lahteenmaki, L., Crittenden, R., Salminen, S. & Mattila-Sandholm, T. (2002) Gut bacteria and health foods–the European perspective. Int. J. Food Microbiol. 78:99-117.[Medline]
50. Kalliomaki, M., Salminen, S., Arvilommi, H., Kero, P., Koskinen, P. & Isolauri, E. (2001) Probiotics in primary prevention of atopic disease: a randomised placebo-controlled trial. Lancet 357:1076-1079.[Medline]
51. Bengmark, S. (2001) Pre-, pro- and synbiotics. Curr. Opin. Clin. Nutr. Metab. Care 4:571-579.[Medline]
52. D’Souza, A. L., Rajkumar, C., Cooke, J. & Bulpitt, C. J. (2002) Probiotics in prevention of antibiotic associated diarrhoea: meta-analysis. Br. Med. J. 324:1361.
53. Marteau, P., Seksik, P. & Shanahan, F. (2003) Manipulation of the bacterial flora in inflammatory bowel disease. Best. Pract. Res. Clin. Gastroenterol. 17:47-61.[Medline]
54. Kleessen, B., Kroesen, A. J., Buhr, H. J. & Blaut, M. (2002) Mucosal and invading bacteria in patients with inflammatory bowel disease compared with controls. Scand. J. Gastroenterol. 37:1034-1041.[Medline]
55. Pool-Zobel, B., van Loo, J., Rowland, I. & Roberfroid, M. B. (2002) Experimental evidences on the potential of prebiotic fructans to reduce the risk of colon cancer. Br. J. Nutr. 87(Suppl 2):S273-S281.
56. Kampman, E., Giovannucci, E., Vantveer, P., Rimm, E., Stampfer, M. J., Colditz, G. A., Kok, F. J. & Willet, W. C. (1994) Calcium, vitamin D, dairy foods, and the occurrence of colorectal adenomas among men and women in two prospective studies. Am. J. Epidemiol. 139:16-29.
57. Kearney, J., Giovannucci, E., Rimm, E. B., Ascherio, A., Stampfer, M. J., Colditz, G. A., Wing, A., Kampman, E. & Willet, W. C. (1996) Calcium, vitamin D, and dairy foods and the occurrence of colon cancer in men. Am. J. Epidemiol. 143:907-917.
58. Rafter, J. (2002) Lactic acid bacteria and cancer: mechanistic perspective. Br. J. Nutr. 88(Suppl 1):S89-S94.
59. Wu, S., Morin, P. J., Maouyo, D. & Sears, C. L. (2003) Bacteroides fragilis enterotoxin induces c-Myc expression and cellular proliferation. Gastroenterology 124:392-400.[Medline]
60. Wu, S., Lim, K. C., Huang, J., Saidi, R. F. & Sears, C. L. (1998) Bacteroides fragilis enterotoxin cleaves the zonula adherens protein, E-cadherin. Proc. Natl. Acad. Sci. U.S.A. 95:14979-14984.
61. Pitari, G. M., Zingman, L. V., Hodgson, D. M., Alekseev, A. E., Kazerounian, S., Bienengraeber, M., Hajnoczky, G., Terzic, A. & Waldman, S. A. (2003) Bacterial enterotoxins are associated with resistance to colon cancer. Proc. Natl. Acad. Sci. U.S.A. 100:2695-2699.
62. SEER (2003) Cancer Statistics 2003 NCI SEER.
63. World Cancer Research Fund (1997) Food, Nutrition, and the Prevention of Cancer: A Global Perspective 1997 American Institute for Cancer Research Washington, DC.
64. Higginson, J. (1968) The theoretical possibilities of cancer prevention in man. Proc. R. Soc. Med. 61:723-726.[Medline]
65. Colditz, G. A. (2003) Lifestyle behaviours contributing to the burden of cancer. Curry, S. J. Byers, T. Hewitt, M. eds. Fulfilling the Potential of Cancer Prevention and Early Detection 2003:41-86 NCBP, IOM. The National Academies Press Washington, DC .
66. Giovannucci, E., Rimm, E. B., Stampfer, M. J., Colditz, G. A., Ascherio, A. & Willett, W. C. (1994) Intake of fat, meat, and fiber in relation to risk of colon cancer in men. Cancer Res 54:2390-2397.
67. Hill, M. J. (1995) Diet and cancer: a review of scientific evidence. Eur. J. Cancer Prev. 4(Suppl 2):3-42.[Medline]
68. Dove, W. F., Clipson, L., Gould, K. A., Luongo, C., Marshall, D. J., Moser, A. R., Newton, M. A. & Jacoby, R. F. (1997) Intestinal neoplasia in the ApcMin mouse: independence from the microbial and natural killer (beige locus) status. Cancer Res 57:812-814.
69. Newman, J. V., Kosaka, T., Sheppard, B. J., Fox, J. G. & Schauer, D. B. (2001) Bacterial infection promotes colon tumorigenesis in Apc(Min/+) mice. J. Infect. Dis. 184:227-330.[Medline]
This article has been cited by other articles:
|
|
 |
|
  O. Paliy, H. Kenche, F. Abernathy, and S. Michail High-Throughput Quantitative Analysis of the Human Intestinal Microbiota with a Phylogenetic Microarray Appl. Envir. Microbiol., June 1, 2009; 75(11): 3572 - 3579. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 O. Schreiber, J. Petersson, M. Phillipson, M. Perry, S. Roos, and L. Holm Lactobacillus reuteri prevents colitis by reducing P-selectin-associated leukocyte- and platelet-endothelial cell interactions Am J Physiol Gastrointest Liver Physiol, March 1, 2009; 296(3): G534 - G542. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 R. Balamurugan, H. P Janardhan, S. George, S. P. Chittaranjan, and B. S Ramakrishna Bacterial succession in the colon during childhood and adolescence: molecular studies in a southern Indian village Am. J. Clinical Nutrition, December 1, 2008; 88(6): 1643 - 1647. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. Kuehbacher, A. Rehman, P. Lepage, S. Hellmig, U. R. Folsch, S. Schreiber, and S. J. Ott Intestinal TM7 bacterial phylogenies in active inflammatory bowel disease J. Med. Microbiol., December 1, 2008; 57(12): 1569 - 1576. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. Iapichino, M. L. Callegari, S. Marzorati, M. Cigada, D. Corbella, S. Ferrari, and L. Morelli Impact of antibiotics on the gut microbiota of critically ill patients J. Med. Microbiol., August 1, 2008; 57(8): 1007 - 1014. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. Penders, C. Thijs, P. A van den Brandt, I. Kummeling, B. Snijders, F. Stelma, H. Adams, R. van Ree, and E. E Stobberingh Gut microbiota composition and development of atopic manifestations in infancy: the KOALA Birth Cohort Study Gut, May 1, 2007; 56(5): 661 - 667. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. Drisko, B. Bischoff, M. Hall, and R. McCallum Treating Irritable Bowel Syndrome with a Food Elimination Diet Followed by Food Challenge and Probiotics J. Am. Coll. Nutr., December 1, 2006; 25(6): 514 - 522. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. D. Scanlan, F. Shanahan, C. O'Mahony, and J. R. Marchesi Culture-Independent Analyses of Temporal Variation of the Dominant Fecal Microbiota and Targeted Bacterial Subgroups in Crohn's Disease J. Clin. Microbiol., November 1, 2006; 44(11): 3980 - 3988. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. M. Ridlon, D.-J. Kang, and P. B. Hylemon Bile salt biotransformations by human intestinal bacteria J. Lipid Res., February 1, 2006; 47(2): 241 - 259. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. R. Frederick and W. A. Petri Jr. Roles for the galactose-/N-acetylgalactosamine-binding lectin of Entamoeba in parasite virulence and differentiation Glycobiology, December 1, 2005; 15(12): 53R - 59R. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K. Whelan, P. A. Judd, V. R. Preedy, R. Simmering, A. Jann, and M. A. Taylor Fructooligosaccharides and Fiber Partially Prevent the Alterations in Fecal Microbiota and Short-Chain Fatty Acid Concentrations Caused by Standard Enteral Formula in Healthy Humans J. Nutr., August 1, 2005; 135(8): 1896 - 1902. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Atkinson, C. L. Frankenfeld, and J. W. Lampe Gut Bacterial Metabolism of the Soy Isoflavone Daidzein: Exploring the Relevance to Human Health Exp Biol Med, March 1, 2005; 230(3): 155 - 170. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Schenk, A. Bouchon, S. Birrer, M. Colonna, and C. Mueller Macrophages Expressing Triggering Receptor Expressed on Myeloid Cells-1 Are Underrepresented in the Human Intestine J. Immunol., January 1, 2005; 174(1): 517 - 524. [Abstract] [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
