Gut microbial composition of the kinship relationships resemble with each other more than unrelated individuals (Dicksved and others 2008; Turnbaugh and others 2009c), suggesting that the genetic background may be an important factor in selecting and shaping the intestinal microbiota. A study of 645 mice with the use of quantitative trait loci (QTL) detection approach (an analysis to test whether specific taxa cosegregate as quantitative traits with linked genomic markers) revealed that for 18 host QTL, the host genetic variation is correlated with relative abundances of specific microbial taxa, including at least one taxon from each of the Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria phyla (Benson and others 2010). Another clinical study of familial Mediterranean fever (FMF) patients by mutations in the MEFV gene—which encodes the pyrin, a regulatory protein of innate immunity demonstrated significant shifts in bacterial community structure such as decreased total numbers of bacteria, lower diversity, and major changes in bacterial populations within the Bacteroidetes, Firmicutes, and Proteobacteria phyla (Khachatryan and others 2008).
These findings highlight that there is an interaction between the host genetics and a specific profile of commensal microbiota in the human gut, which will be critical for future studies to understand the association between the composition of gut microbiota and complex diseases.
The gut microbiota in various age groups present different characteristics (Figure 1). To realize the significant features of each group and the reasons for them will help to enhance pertinence and actual effects of further studies.
Infancy is a critical period for intestinal colonization. The newborn infant gastrointestinal tract is almost sterile and initial acquisition of infant gut microbiota can be from vagina, feces, and hospital. The early colonizers after delivery mainly are Bifidobacterium, Clostridium, Ruminococcus, Enterococcus, Enterobacter, and Bacteroides (Favier and others 2002; Marques and others 2010). During the first 2 y of life, the composition of the infant intestine is volatile and susceptible to many factors (O'Toole and Claesson 2010) including delivery mode (Adlerberth and Wold 2009; Dominguez-Bello and others 2010), feeding method (Orrhage and Nord 1999), and environmental factors (such as health care, nutrition, and antibiotics). Accompanied by the fluctuations of bacterial populations, the complexity of the bacterial community evolved gradually toward an adult-like configuration (Palmer and others 2007; EGGESBø and others 2011; Yatsunenko and others 2012).
In adulthood, the gut microbial composition is relatively stable and dominated by Firmicutes and Bacteroidetes. Although it undergoes multiple perturbations of diets, antibiotics, and/or new species invasion, the conventional microbiota can protect against changes to a certain extent. But if the perturbations overload the capacity of the microsystem can tolerate, shifts in gut microbiota occur and may induce dysbacteriosis resulting in a range of diseases (Lozupone and others 2012).
The human gut microbiota undergoes substantial changes through the aging process as well as the functionality of the host immune system, resulting in a frail situation and a greater susceptibility to infections. Several studies have observed age-related changes in the gut microbiota composition. For example, The dominant roles of Firmicutes and Bacteroidetes keep unchanged during different life stages but the ratio of Firmicutes to Bacteroidetes evolves—to be respectively 0.4, 10.9, and 0.6 for infants, adults, and elderly individuals (Mariat and others 2009).
In a study explored the gut microbiota composition of 145 elderly (mean age, 75 y) people and 85 health adults (mean age, 35 y) from 4 European countries, higher prevalence of Enterobacteria were found in all subjects independent of the location (Mueller and others 2006). Another published study probed into the age-related differences in the gut microbial composition among young adults, elderly (mean age, 70 y), and centenarians (>100-y old) observed highly similarity in that of the former 2 groups, whereas that of the centenarians showed highly difference. In the centenarians, Eubacterium limosum and relatives representative of the long life were more than 10-fold increased. Additionally, the proportion of facultative anaerobes enriched. By contrast, a marked decrease of Bifidobacteria, Faecalibacterium prauznitzii, and relative symbiotic species with reported anti-inflammatory properties was observed in centenarians (Biagi and others 2010). All these findings suggest that the gut microbial composition of the elderly vary from those in adults.
The innate alteration of human gut microbiota with ageing may have relation to some symptoms of aging such as lower gastrointestinal function (Štšepetova and others 2011). Better understanding of the features presented by different age ranges will help to find the relationship between gut microbiota and age-related illness, and further clarify the pathogenesis.
Dietary effects on gut microbiota
Dietary regulation to the gut microbiota of early life
The development of gut community in early life is important to shape the intestinal microbiota and immune system of the host in later life (Olszak and others 2012).
Feeding type is one of the most essential factors that affect the neonate gut microbiotic composition. Breast-fed infants were mainly colonized with bifidobacteria (up to 90% of flora). Human milk oligosaccharides (HMOs) are considered functioning as growth factors for beneficial gut bacteria, as inhibitory receptors binding to different pathogens, and may promote development of the early immune system (Kunz and others 2000; Hemarajata and Versalovic 2012). In contrast, bottle-fed infants harbor more diverse microbiota groups including Bacteroides, Clostridium, and Enterobacteriaceae (Martin and Walker 2008; Martín and others 2009). The more reasonable nutrition designed formulas nowadays, which contain prebiotics such as galactooligosaccharides (GOS) and fructooligosaccharides (FOS), have been proven to increase the number of Bifidobacteria and Lactobacilli in the gut.
In contrast, antibiotics play a negative role in the composition of the infant gut microbiota, resulting in decrease of obligate anaerobes (for example, Bifidobacteria and Bacteroides; Martin and Walker 2008; Reinhardt and others 2009). Reduced bacterial diversity of the infant's intestinal flora precedes asthma (Abrahamsson and others 2013), allergic sensitization, allergic rhinitis, and peripheral blood eosinophilia in the childhood (Bisgaard and others 2011). However, the gut microbiota effect vary with antibiotics (Penders and others 2006). Decreasing excessive use of antibiotics and increasing the use of pre- and probiotics is effective in preventing several important infant diseases such as necrotizing enterocolitis, atopic eczema as well as improving short and long-term health (Wall and others 2009).
To sum up, dietary modulation to the infant microbiota influences the developing immune system and thus affect immunological response to some pathogens in later life.
Long-term dietary regulation derived from different cultures
Dietary history is associated with geography, cultural practices, lifestyle, and socioeconomic status. Significant differences have been found among the gut microbiota of the Russian, American, Danish, and Chinese groups (Tyakht and others 2013). Similarly, comparisons have also been made between Korean gut microbial communities and those members from other countries including the USA, China, and Japan. UniFrac analysis revealed that fecal microbial community of each country member showed slight difference from each other at phyla level, with American had higher Firmicutes, Japanese had higher Actinobacteria, and Korean and Chinese enriched in Bacterodetes (Nam and others 2011). Thereby, gut microbial composition is likely linked to long-term dietary style.
The intestinal microbiomes of rural children in Burkina Faso who consumed a plant-rich diet were compared with that of children from Italy who consumed a low-fiber diet (De Filippo and others 2010) and significant differences of gut flora and opposite trend between the 2 groups were gotten: the African children had lower levels of Firmicutes than of Bacteroidetes whereas the European children who had high levels of Enterobacteriaceae (Shigella and Escherichia). In specific, the dominant genera of bacteroides in the microbiota of African children were the Prevotella and Xylanibacter, whereas those of the European children were the genera Bacteroides and Alistipes. Prevotella and Xylanibacter can ferment both xylan and cellulose in the rural diet of the African children to liberate energy. The Bacteroides plebeius coding genes of porphyranases and agarases are significantly more frequent in the gut microbiome of Japanese than that of the North American population, which is associated with the seaweeds-rich diet habits of Japanese since seaweeds is a major resource of the Bacteroides plebeius (Hehemann and others 2010). Significant differences in the phylogenetic composition of fecal microbiota were noted between U.S. residents and those from Malawians and Amerindians (Yatsunenko and others 2012). At species level, the non-U.S. adults had a higher prevalence of the Prevotella genus than the U.S. residents. The enzyme composition (EC) representation in fecal microbiomes was also compared to see if the distinctive features are evident. The ECs participates in the catabolism of glutamine, simple sugars, sugar substitutes, and host glycans have higher proportional representation in adult U.S. fecal microbiomes, reflecting their typical western diet. In contrast, the EC involved in the degradation of starch was at high level in the Malawian and Amerindian microbiomes, reflecting their corn-dominant diet (Yatsunenko and others 2012) .
The metagenomes of gut microbiota community structures from Russian cities resembled those of Western countries, which is presumably associated with increased consumption of meat products and processed food (Tyakht and others 2013). However, the gut microbiota in rural residents of Russia are distinctly enriched in Firmicutes and Actinobacteria (both are underrepresented in urban residents), which is presumably associated with high consumption of starch-rich bread and natural products (Tyakht and others 2013).
These findings imply that the dietary habits formed over a long period of time may play a key role in the composition of gut microbiota over other variables such as ethnicity, sanitation, and climate. But the genetic differences in individuals among different countries cannot be neglected. More carefully controlled studies should be carried out to probe into the relationship between long-term dietary patterns and gut microbiota even without genetic factors and other environmental variables.
Short-term regulation by diet patterns and food ingredients
Food ingredients such as polysaccharides, fat, protein, and vitamins consumed by the host can be absorbed and utilized by gut microbiota. The microbial species in humans gut can be more adept at degrading polysaccharides than the hosts themselves, resulting in higher production of short-chain fatty acids (SCFAs) such as acetate, propionate, and butyrate. Different microbial species have their preferential “targets,” and diet–microbe interactions within the gut are now thought to play an important role in host health with links to suppression of pathogens, impact on blood lipids, and a reduced risk of developing metabolic disorders (Costabile and others 2008). The research about the diet-related effects on the gut microbiota is of great significance for the human health. For example, the vegetarian diet and the Western diet are 2 distinctly different diet patterns, in which the former is characterized by high fiber and low fat and the latter is the other way around. Several studies have detected the difference of the gut flora composition between the 2 diet patterns. The gut microbiota of vegetarians is dominated by Clostridium coccoides, Clostridium ramosum (Finegold and others 1983; Hayashi and others 2002) and in the absent of Faecalibacterium prausnitzii (Hayashi and others 2002). The clusters of F. prausnitzii were found at high levels in groups who mainly consume fish and meat (Mueller and others 2006).
A more strict-designed recent study observed a vegan or vegetarian diet can significantly change the human gut microbiota compared with the omnivorous controls carefully matched for age and gender. Specifically, a distinct decrease in the counts of Bacteroides spp., Bifidobacterium spp., Escherichia coli, and Enterobacteriaceae spp. was found in vegans and vegetarians (Zimmer and others 2011), whereas the total bacteria cells were unchanged. A shift in the fluctuant nonstarch polysaccharides and some other nutrients from meal can rapidly alters the composition of the microbiota (Turnbaugh and others 2009b; Sonnenburg and others 2010; Faith and others 2011; Goodman and others 2011).
Whole grain cereal is rich in dietary fiber and resistant starch (RS) with protection from chronic diseases. A recent in vitro study explored the impact of 2 different sized oat flakes on the human gut microbial ecosystem (Connolly and others 2010a). The larger one produced significant increases in Bifidobacterium in the latter stages of fermentation whereas numbers declined for the smaller one. Additionally, the smaller one resulted in a significant increase in the Bacteroidese Prevotella group. The differences may be due to varying types and levels of dietary fiber present after digestion in particular RS (Bifidobacterium are known to ferment this dietary fiber; Connolly and others 2010a).
A study of 10 human subjects under a controlled setting detected marked changes in the microbiota along with a dietary shift from high-fat, low-fiber to low-fat, high-fiber diets within 24 h (Wu and others 2011). But the short time was not sufficient to change the dominant enterotypes distinguished primarily by levels of Bacteroides (associated with protein and animal fat) and Prevotella (associated with carbohydrates). Thus, altering enterotypes may require a long-term dietary intervention, more in line with the study comparing children from Italy and Burkina-Faso (De Filippo and others 2010; Wu and others 2011). A recent study of 14 overweight men with precisely controlled diets revealed rapid and marked changes in the colonic microbiota and demonstrated the influence of dietary intake with consequences for health (Walker and others 2010). In this study, the subjects were provided successively with a control diet, diets high in resistant starch (RS) or nonstarch polysaccharides (NSPs), and a low carbohydrate weight loss (WL) diet. Detected by qPCR, Firmicutes bacteria related to Ruminococcus bromii (R-ruminococci) and Eubacterium rectale increased in most volunteers on the RS diet, and the Oscillibacter group was enhanced by both the RS and WL diets. The E. rectale decreased, along with Collinsella aerofaciens, on WL diet. However, the starch digestibility estimated from chemical analysis of the diet and of 24 h fecal samples were subject to interindividual variation, with >60% of RS remaining unfermented in 2 volunteers on the RS diet, compared to <4% in the other 12 volunteers. These results may be due to profound differences in the response of the microbial community to dietary change, and in microbial fermentation of dietary substrates in the colon between individuals (Walker and others 2010).
It has been shown that diets high in RS and NSP can respectively benefit insulin sensitivity and phytochemicals release through the microbial fermentative activity in the colon (Gill and Rowland 2002; Robertson and others 2005). Besides, diets containing RS and NSP offer potential benefits in prevention of colorectal cancer through the delivery of fermentation acids, in particular butyrate, to the distal colon (McIntyre and others 1993; Duncan and others 2007). Additionally, studies have found that WL diets have considerable influence on the composition and metabolic outputs of the gut bacterial community (Duncan and others 2007, 2008; Brinkworth and others 2009) .
Probiotics are defined as “live microorganisms which, when administered in adequate amounts to allow colonization of the colon, confer a health benefit on the host” (Sanders 2008), of which the most common groups are the genera Lactobacillus and Bifidobacterium (Parracho and others 2007). Introducing probiotics to human and mice can lead to variations in expression of microbiome-encoded enzymes associated to plant polysaccharide metabolism (McNulty and others 2011). Probiotics have been shown to maintain the normal microbial community structure, inhibit the invasion of pathogens in the human gut by increasing the amount of mucus secretion, improve the mucosal integrity, and reduce the gut permeability (Spinler and others 2008; Saulnier and others 2009; O'Shea and others 2012; Shen and others 2013). The ability of Bifidobacteria to improve gut barrier function and reduce the intestinal endotoxin levels has been demonstrated in several studies (Griffiths and others 2004; Wang and others 2004; Wang and others 2006). Furthermore, probiotics can act on the gut immune system and affect the gut epithelia and immune cells sensitivity to microbes in the gut lumen (Thomas and Versalovic 2010). The potential use of probiotics in lowering necrotizing enterocolitis risks in preterm infants and preventing infections in immunocompromised patients are also discussed in some studies (Martin and Walker 2008; Guillemard and others 2010; Mikelsaar and others 2010; Tatum and others 2010).
Moreover, probiotics may function as a supplementary tool to ameliorate obesity and associated disorders (Shen and others 2013; Sommer and Bäckhed 2013). A study on diet-induced obese mice has confirmed the anti-obesity effect of Lactobacillus rhamnosus PL60, a human originated bacterium (Lee and others 2006). Another germ-free mice study revealed that Lactobacillus paracasei could decrease fat storage along with a high level of Angptl4, which is a circulating lipoprotein lipase (LPL) inhibitor that controls triglyceride deposition into adipocytes (Aronsson and others 2010).
As growth promoters, probiotics have been widely used in the animal farming industry for nearly 50 y, and are experimentally shown to stimulate fattening in poultry (Angelakis and Raoult 2010), livestock (Anadón and others 2006) and mice (Angelakis and others 2012). It is difficult to deny the hypothesis that probiotics may have the same effect in humans by altering the intestinal flora. High level of intestinal lactobacilli can increase risks of obesity and hyperglycemia in healthy adults (Štšepetova and others 2011), but the effects of the probiotics for body weight and obesity are deemed to be strain specific. For example, Lactobacillus ingluviei, Lactobacillus acidophilus are associated with a weight-gain effect, whereas Lactobacillus casei/paracasei, Lactobacillus plantarum, and Lactobacillus gasseri showed antiobesity effect (Million and others 2011, 2012). In a rats study compared the effects of 4 Bifidobacteria strains on the body weight (BW) gains acquired different results: 1 strain increased BW, 1 strain reduced BW, and the rest 2 had no significant influences on BW (Yin and others 2010). Therefore, the supplementation of probiotics should be detailed in specific strains and carefully evaluated before they are regarded as safe for human use.
Prebiotics refers to nondigestible food ingredients that selectively stimulate the growth of one or a limited number of microbes in the gut with beneficial effects for host health (Pharmaceutiques 1995; Roberfroid 2007; Saulnier and others 2009; Roberfroid and others 2010).
The prebiotic-rich foods, such as Jerusalem artichokes and chicory, have been reported the ability to regulate gut microbiota by elevating the number of Bifidobacteria and Lactobacilli (Kleessen and others 2007; Ramnani and others 2010) . To improve their applicability, prebiotics may serve as oral intake ingredients. Supplementation with prebiotics such as fructo-oligosaccharides (FOS) and inulin can promote the growth of beneficial gut bacteria, particularly Bifidobacterium and/or Lactobacillus (Ramirez-Farias and others 2009; Brignardello and others 2010; Maccarrone and others 2010; Roberfroid and others 2010; Cani and others 2012), and decrease the number of Clostridium leptum in some studies (Pyra and others 2012). Interestingly, some fructans are also able to increase other bacteria such as F. prausnitzii (Ramirez-Farias and others 2009).
Several mechanisms (Table 1) have been proposed to illustrate the beneficial effects of prebiotic on obesity and related metabolic disease such as type 2 diabetes and several cardiovascular disease : (1) a modulation of gut peptides (glucagon-like peptide 1, peptide YY, and intestinal proglucagon mRNA) with consequences for a decrease in appetite and postprandial glucose excursion responses (Cani and others 2009a; Parnell and Reimer 2009; Everard and others 2011; Hess and others 2011). (2) Increasing endogenous glucagon-like peptide-2 (GLP-2) production resulting in the amelioration of gut barrier functions during obesity and diabetes (Cani and others 2009b). (3) Improving glucose tolerance, target enteroendocrine cell activity, and leptin sensitivity associated with metabolism in obesity and diabetes (Cani and others 2009b; Everard and others 2011). (4) Promoting gut fermentation and modulating GPR43 (a G protein-coupled receptor, linking between gut fermentation processes and white adipose tissue development) expression, thus controlling the development of adipose tissue (Dewulf and others 2011). (5) Regulating inflammatory tone by a decrease in endotoxaemia, plasma, and adipose tissue proinflammatory cytokines, as well as hepatic expression of inflammatory and oxidative stress markers, which may affect host metabolism in obesity and diabetes (Cani and others 2007, 2009b).
Table 1. Studies of the mechanisms and beneficial effects of prebiotics on obesity and related metabolic disease
|HF-feeding mice vs normal chow-fed control mice and HF-OFS-treated mice||Bifidobacterium spp.↑||Glucose tolerance↑, glucose-induced insulin secretion↑；normalized inflammatory tone endotoxaemia↓, plasma and adipose tissue proinflammatory cytokines↓||Improving high-fat-diet-induced diabetes in mice||Cani and others 2007|
|10 healthy adults (5 men and 5 women) were randomly divided into 2 groups: received either 16 g prebiotics/d or 16 g dextrin maltose/d for 2 wk|| ||Plasma glucagon-like peptide 1↑ and peptide YY concentrations↑||Changes in appetite sensation and glucose excursion responses after a meal||Cani and others 2009a|
|1. ob/ob mice (Ob-CT): prebiotic treatment (Ob-Pre) vs control (Ob-Cell) 2. Ob-CT and Ob-Pre mice were treated with GLP-2 antagonist or saline 3. Ob-CT mice were treated with a GLP-2 agonist or saline||Bifidobacterium spp.↑||Inflammatory tone (plasma LPS and cytokines↓, hepatic expression of inflammatory and oxidative stress markers↓); the endogenous intestinotrophic proglucagon-derived peptide (GLP-2) production↑, intestinal permeability↓||Improving inflammation and metabolic disorders during obesity and diabetes; improve gut barrier functions||Cani and others 2009a|
|ob/ob mice or diet-induced obese and diabetic mice: chronically fed with prebiotic-enriched diet or with a control diet||Firmicutes ↓ Bacteroidetes ↑||Glucose tolerance↑, L-cell number↑(intestinal proglucagon mRNA expression ↑and plasma glucagon-like peptide-1 levels↑), fat-mass development↓, fat oxidative stress↓, and low-grade inflammation↓, leptin sensitivity↑||Exerting effects on host metabolism in obesity and diabetes||Everard and others 2011|
|Male C57bl6/J mice: fed a standard diet or an HF diet without or with Inulin-type fructans (ITF) (0.2 g/d per mouse) during 4 wk||Bifidobacterium spp.↑ Roseburia spp. ↓ C. coccoides↓||Peroxisome proliferator activated receptor γ (PPAR-γ)–activated differentiation factors↓, GPR43 expression↓, the subcutaneous adipose tissue↓||A beneficial effect on obesity and with potential decrease in PPAR-γ–activated processes||Dewulf and others 2011|
|Male lean and obese JCR:LA-cp rats: received different dose of inulin and oligofructose||Firmicutes↓ Bacteroidetes ↑ Bifidobacteria and Lactobacillus↑(in a dose-dependent manner)||Caecal proglucagon and peptide YY mRNA levels↑, plasma ghrelin response↓ (in a dose-dependent manner)||Dose-dependent regulation of the appetite effects and energy expenditure may have therapeutic potential for obesity||Parnell and Reimer 2012|
|20 healthy subjects: assigned to receive 2 separate doses of 0, 5, or 8 g of short-chain fructooligosaccharide (scFOS)|| ||Gastrointestinal tolerance ↑, breath hydrogen↑(in a dose-dependent manner ), the appetite effects was not obvious||The potential of scFOS as a dietary intervention is still remained to be seen||Hess and others 2011|
|48 healthy adults with a body mass index (in kg/m2) > 25 consumed 21 g oligofructose/d or a placebo (maltodextrin) for 12 wk|| ||Plasma ghrelin response↓ and peptide YY↑||The potential to promote weight loss and ameliorate satiety hormone concentrations and glucose regulation in overweight adults||Parnell, and Reimer 2009|
|Male, diet-induced obese Sprague–Dawley rats: fed with high-fat/-sucrose diet plus either metformin (MET) or oligofructose (OFS) or both||Bifidobacteria ↑ Clostridium leptum ↓||Fat mass↓, hepatic total glycerin↓, glucose-dependent insulinotropic polypeptide (GIP) secretion↓, leptin↑, AMPKα2 mRNA and phosphorylated acetyl CoA carboxylase (pACC) levels↑, plasma DPP4 activity↓||The potential to improve metabolic outcomes associated with obesity||Pyra and others 2012|
Antibiotics are designed to target pathogenic population and improve our lives by treating infectious diseases. But because most of them have broad-spectrum activity, they can affect other members of the gut microbiota and thereby disrupt their coevolved interactions with the host.
The alterations in the gut microbiota as a result of antibiotic treatment mainly come down to a shift in microbiota composition (Dethlefsen and others 2008; Dethlefsen and Relman 2011), reduced diversity, and/or abundance of bacteroides (Dethlefsen and others 2008; MacFarlane and Macfarlane 2009; Dethlefsen and Relman 2011), and decreased evenness of the community (Dethlefsen and others 2008). But community changes induced by antibiotic treatment varied among individuals, which may be due to the expansion of antibiotic-resistant genes in the gut microenvironment and other indirect factors (Dethlefsen and others 2008).
Disrupted interactions within the gut flora resulting from antibiotic usage are reported in associated with acute (Beaugerie and Petit 2004) and chronic (Flöistrup and others 2006; Marra and others 2006) health problems, such as obesity (Ternak 2005), diarrhea, asthma, and IBD (Guarner and others 2006). Significant and persistent weight gain can occur after treatment with a 6-wk intravenous treatment of vancomycin in patients with infective endocarditis, which might be due to the selection of Lactobacillus sp. in the gut microbiota (Thuny and others 2010). Antibiotic therapy can also prevent from obesity as well as improve plasma lipopolysacharides (LPS) levels and glucose tolerance (Kalliomäki and others 2008; Membrez and others 2008).
A study of the infant gut flora following ampicillin and gentamicin treatment indicated that the gut microbiota of the antibiotic-treated infants significantly changed (with a higher proportions of Proteobacteria and lower proportions of Actinobacteria as well as the genus Lactobacillus than the untreated counterparts) and recovery still incomplete after 8 wk, which suggests antibiotics disruption in early life can exert crucial influences on the evolution of the infant gut microbiota (Fouhy and others 2012).
Although the composition of human gut microbiota changes naturally with age, the impact of antibiotic therapy on the elderly intestinal microbiota composition taking into account their residence location (long-term nursing care, rehabilitation wards, day hospitals, and the community) was recently discussed (O'Sullivan and others 2013). The study revealed that a significant structural shift across 9 genera in the antibiotic-treated subjects, including a 7-fold reduction in Bifidobacterium spp. numbers. Thus, the long-term health effects following antibiotic therapy on the intestinal microbiota in the elderly should be considered (O'Sullivan and others 2013).
The mechanisms of the microbiota modulation toward host metabolic and immune system induced by antibiotic treatment are complex and largely unclear. The known hypothesizes at present may include (1) Effects on microbial intestinal metabolism: gut bacteria respond to antibiotic usage attenuated the production of SCFAs—which is the main energy source and associated with cell proliferation, differentiation, growth, and apoptosis (Willing and others 2011)—and the capacity to transport and metabolize bile acid, cholesterol, hormones, and vitamins (Pérez-Cobas and others 2013). (2) Perturbation in intestinal homeostasis and the integrity of intestinal defenses: a study with metronidazole-treated mice indicated that disruption of the microbiota with antibiotic resulted in an increased inflammatory tone of the gut, which is characterized by increased bacterial (C. rodentium) stimulation of the epithelium, altered goblet cell function, and reduction in mucus thickness. It demonstrates a impaired mucosal barrier and thus contributes to the exacerbated severity of C. rodentium-induced colitis (Wlodarska and others 2011). (3) Distribution to the innate immunity: lower diversity of the microbiota following antibiotic treatment can decrease the amount of microorganism-associated molecular pattern (MAMP) recognition receptors, for example Toll-like receptors (TLRs), which are activated by bacterial ligands and thereby weakening the innate immunity (Dessein and others 2009; Wells and others 2010). (4) Regulation of T-cell differentiation and activation: depleting Gram-positive bacteria especially segmented filamentous bacteria population with antibiotics reduces the differentiation of T-helper 17 cells, thus resulting in a depletion of the secretion of related pro-inflammatory cytokines (Ivanov and others 2009).