Monday, 2 October 2017

SEMINAR PRESENTATION ON BCH 411 FRONTIERS IN BIOCHEMISTRY, MOLECULAR BIOLOGY AND BIOTECHNOLOGY TOPIC:THE ROLE OF GUT MICROBIOTA IN THE DEVELOPMENT OF DIABETES AND OBESITY. PRESENTED BY OBINWA MARY-ANN UKAMAKA REG NO: 2012474143 DEPARTMENT OF APPLIED BIOCHEMISTRY FACULTY OF BIOSCIENCES NNAMDI AZIKIWE UNIVERSITY,AWKA. SUPERVISOR: MR.NWAJIOBI JIDE DATE:DECEMBER, 2016 A ABSTRACT A recent growing number of evidences show that the increased prevalence of obesity and diabetes cannot be attributed to changes in the human genome, nutritional habits, or reduction in physical activity in our daily lives Gut microbiota may play an even an more important role in maintaining human health, as it function much like a “metabolic organ” influencing nutrient aquisition, energy homeostasis and, ultimately, the control of the body weight. Moreover, alterations in gut microbiota can lead to increase intestinal permeability, and metabolic endotoxemia which play a rolesss in the development of chronic low grade inflammatory state in the host that contributes to the development of obesity and diabetes. However the fact that gut microbiota can be modulated through dietary components highlights the importance to study how fatty acid, carbohydrates, probiotics, can influence gut microbiota composition and management of obesity. Gut microbiota seems to be an important and promising target in the prevention and treatment of obesity and its related metabolic disturbances. INTRODUCTION The epidemics of obesity and type 2 diabetes mellitus in the past 20 years have led to numerous investigations concerning the mechanisms that are responsible for the development of these diseases. The general view is that insulin resistance is an early alteration of type 2 diabetes mellitus and obesity, and both diseases are strongly influenced by genetics and environment. Moreover, studies in the past ten years have shown that low-grade inflammation has an important role in the molecular mechanism of insulin resistance in these diseases and more recently (within the past five years) a new component that has both genetic and environmental factors is also being studied: the gut microbiota. This way, a paradigm has been dismantled: microorganisms should no longer be associated with pathogenesis, since both bacteria and their eukaryote hosts benefit from their cooperative relationships. In humans, there are at least 100 trillion microbial cells, collectively called microbiota, distributed in complex and site-specific communities. As the genome of these bacteria—the microbiome—contains hundreds of genes that do not exist in the human genome, we can consider our symbionts as an important extra organ. This complex community—bacteria, eukaryotes, viruses and Archeae—in its majority cannot be cultured. The reasons for this limitation are unknown growth requirements of the bacteria, selectivity of the media that are used, stress imposed by the cultivation procedures, necessity of strictly anoxic conditions, and the difficulties on simulating the interactions of bacteria with other microbes and host cells. Thus, a new approach was introduced, culture-independent sequencing, which made detection of microbial genes and disease-associated patterns in our gut microbiota possible. The bacterial component of the microbiota has been intensively studied in the past few years, including high-investment studies such as the Human Microbiome Project and MetaHIT. Using this new approach made it possible to detect three dominating bacterial phyla in the human gastrointestinal tract: the gram-positive Firmicutes and Actinobacteria, and the gram-negative Bacteroidetes. Firmicutes is known as the largest bacterial phylum, comprehending 200 genera, which includes Lactobacillus, Mycoplasma, Bacillus, and Clostridium. In spite of Actinobacteria being also a dominant phylum, it is usually missed by RNA gene sequencing and can only be detected by fluorescent in situ hybridization. Although gut microbiota has been described as relatively stable concerning its composition until old age, this temporal consistency considers that numerous variables are being held constant. For example, dietary changes have been shown to have significant effects on the microbiota. Shifting mice to a high-fat, high-sugar ―Western‖ diet, from a low-fat, plant polysaccharide-rich diet, changed the microbiota within 24 hours . Likewise, shifting from a high-fat/low-fiber diet caused notable changes in the gut microbiota within a day. ORIGIN AND COMPOSITION OF GUT MICRIBIOTA The human body contains trillions of microorganisms that inhabit our bodies during and after birth.The gastrointestinal tract starts to be colonized during the delivery of the baby. During the first two years of life de microbiota is unstable and less diverse than in the adulthood, when the complexity and diver-sity is higher. 5 Many external factors influence the composition of the microbiota, especially the diet, the hygiene conditions and the use of antibiotics. 6ing the pregnancy, infant’s intestinal tract is free of mi-crobes until exposed to maternal vaginal microbes during normal birth. Infants born through Caesarian section are exposed to maternal skin bacteria altering their bacterial gut composition. Feeding represents another source of microorganisms where breast fed babies have different gut microbiota composition than formula fed babies(Tanaka et al.,2009). Introduction of solid food represents another shift in the composition of babies gut microbiota. After that, gut microbiota remains relatively unchanged until old age where the composition changes again. Adulthumans have more than 10 times the number of bacterial cells than the cells constituting the human body. Majority of microbiota in the GI tract are bacteria, nevertheless, viruses fungi and other microorganisms are still present. Even though, individuals have unique microbiota composition, gut microbiota is mainly members of four phyla (Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria) ,The distribution of microorganisms throughout the gastrointestinal tract is not homogenous. The stressful environment (gastric juice, bile, pancreatic juice, peri-stalsis) in the stomach and small intestine limits bacte-rial growth and the number of microorganisms.The large intestine contains the highest number of bacteria con-taining over 10 11 bacteria per gram of intestinal con-tent. The mouth contains 10 12 followed by the Ileum containing 10 8 –10 9 bacterial. On the other hand, the jejunum harbors 10 5 –10 6 while the stomach has the least number of bacteria 10 3 –10 4(Othman et al.,2016). The gut microbiota plays different roles that are important for the host. They exert a trophic effect in the intestinal epithelium, favoring the development of the microvilli, which in turn favors the absorption of nutri-ents. The influence of microbiota in innate and adaptive immune system maturation contributes to systemic and local immune homeostasis and immune tolerance for a variety of antigens. The modulation of the immune system activity can influence the intestinal barrier func-tion. The capacity to break down non-digested dietary molecules into metabolites such as short chain fatty acids (SCFS) and to synthesize vitamins demonstrates their importance to human nutrition. Even though we are still far from identifying, let alone characterizing all bacteria in our system, advancing molecular biology techniques such as next-generation sequencing has tremendously contributed to our understanding of the gut microbiota(Ji and Nielsen.,2015). The use of gnotobiological methods to breed mice in a sterile environment provided an invaluable tool to understand the role of infecting con-trolled bacterial cultures and defined bacterial strains into animals. Studying their effect through various genomic and proteomic tools. DIABETES AND GUT MICROBIOTA It’s becoming increasingly evident that gut microbiota is contributing to many human diseases including diabetes both type 1 and type 2. Type 1 diabetes (T1D) is an autoimmune disease that is caused by the destruction of pancreatic β-cells by the immune system. Even though T1D is mainly caused by genetic defect, epigenetic and environmental factors have been shown to play an im-portant role in this disease. Higher rates of T1D inci-dence have been reported in recent years that are not explained by genetic factors and have been attributed to changes in our lifestyle such diet, hygiene, and antibiotic usage that can directly affect microbiota. It has been shown that diabetes incidence in the germ free non-obese diabetic subjects or patients (NOD) was significantly increased which is in line with the observa-tion that the rates of T1D is higher in countries with stringent hygiene practices (Guiden et al.,2015). Similarly comparison of the gut microbiota composition between children with high genetic risk for T1D and their age mhealthy controls showed less diverse and less dynamic microbiota in the risk group. In the Diabetes Pre-vention and Prediction (DIPP) study it was shown that new-onset T1D subjects had different gut microbiota composition than controls(Murri et al., 2013).They showed that in the control group, mucin synthesis was induced by lactate- and butyrate-producing bacteria to maintain gut integrity while mucin synthesis was prevented by the non-butyrate-producing lactate-utilizing bacteria leading to β-cell autoimmunity and T1D (Othman et al.,2016). Recently, research has pointed out that the intestinal microbiome might be an important contributor for the development of type 2 diabetes (T2D). The use of genome-wide association studies (GWAS) has achieved many elucidations in this matter(Qin et al.,2013). characterized the gut microbiota of T2D patients and observed increase in membrane transport of sugars, branched-chain aminoacids transport, methane metabolism, xenobiotics degradation, and sulphate reduction. However, they observed decrease in the levels of butyrate biosynthesis, bacterial chemotaxis, flagellar assembly, vitamins and cofactors metabolism. This study has also shown that the gut environment of T2D individuals is one that stimulates bacterial defense mechanisms against oxidative stress and against drugs. (Andrea and Mario, 2013) GUT MICROBIOTA AND ITS ROLE IN ENERGY HOMEOSTASIS AND THE DEVELOPMENT OF OBESITY The metabolic activities of the gut microbiota have the end results of extracting calories from ingested dietary substances, helping to store those calories in host adipose tissue for later use, and providing energy and nutrients for microbial growth and proliferation. Bäckhed et al 1 dem-onstrated that conventionally raised mice have a 40% higher body fat content and 47% higher gonadal fat con-tent than germ-free (GF) mice, despite lower food intake (Frazier et al 2011). However, it has been suggested that the main routes under influence of gut microbiota that could contribute to obesity develop-ment are provision of extra calories, increased lipopro-tein lipase (LPL) activity, lipogenesis, increased intestinal permeability, endotoxemia and endocannabi-noid (eCB) system (Blaut and Klaus, 2012).Gut microbiota contribute to energy metabolism through the production of SCFA that are produced by colonic fermentation which involves the anaerobic breakdown of dietary fiber, protein and peptides . The most important SCFA produced are acetate, propionate and butyrate. Acetate and propionate are mostly produced by Bacteriodetes phylum while butyrate is produced by the Firmicutes phylum (Othman et all 2016). These SCFA can provide additional calories when they are oxidized by the host, favoring the higher weight and fat gain observed in these animals. In addition, the binding of SCFA to G protein-coupled receptor (GPR) in the intestine induces the secretion of the hormone peptide YY (PYY). This hormone reduces intestinal transit time, increasing the time for nutrient absorption from the intestinal lumen. In fact, obese and overweight subjects presented higher concentration of SCFA in their feces in comparison to lean individuals (Bodoni et al, 2014). Low grade inflammation is a hallmark of obesity. Production of pro- inflammatory cytokines are coordinated via the Toll- like receptors and the master regulator of of key inflammation cascades the nuclear factor kappa(NF-kB) (Kim et al, 2012). The LPL (lipopolysaccharide) activity influences the accumulation of triglycerides in the adipose tissue. The microbiota can affect the activity of this enzyme by the influence on the expression of the protein fasting-induced adipose factor (FIAF). In the absence of microbiota (germ-free mice) it is observed higher expressin of FIAF. 16 On the other hand, the conventionalization of the germ-free animal causes inhibition of the expression of the FIAF and also stimulates body fat gain. It is suggested that FIAF is a circulating inhibitor of LPL activity. Thus, the inhibition of FIAF expression by the presence of microbiota allowus higher activity of LPL and accumulation of triglycerides in adipocytes (Backhad et al, 2004). Figure 2: Alteration in gut microbiota composition due to obesity is accompanied by changes in activation of enzymes and pathways which leads to and increased inflammatory state and energy harvest. AMPK: AMP- activated kinase, SCFA: Short chain fatty acids, LPL: Lipoprotein lipase, ACC: acetyl- CoA carboxylase, CPT1: Carnitine palmitoyltransferase. Source: Andrea and Mario., 2013 THE EFFECT OF GUT MICROBIOTA ON ENERGY METABOLISM The biological functions controlled by the intestinal flora are related to the effectiveness of energy harvest, by the bacteria, of the energy ingested but not digested by the host. Among the dietary compound escaping to the digestion occurring in the upper part of the human gastro-intestinal tract, the polysaccharides constitute the major source of nutrient for the bacteria. Part of these polysaccharides could be transformed into digestible substances such as sugars, or short chain carboxylic acids, providing energy substrates which can be used by the bacteria or the host. The control of body weight depends on mechanisms subtly controlled over time and a small daily excess, as low as 1% of the daily energy needs, can have important consequences in the long term on body weight and metabolism (Hill, 2015). Consequently, the gut microbiota of obese subjects changed according to the loss of body weight occurring after a hypocaloric diet. It was demonstrated that two groups of bacteria are dominant in the intestinal tract, Bacteroidetes and Firmicutes (Cani et al, 2008). The quantification and characterization of each dominant group of bacteria were carried out by measuring the concentration of the bacterial 16S rRNA. The number of Bacteroidetes bacteria depended on the weight loss whereas the Firmicutes bacteria group remained unchanged. Importantly, the bacterial lineage was constant one year after the dietary intervention for a given body weight, validating the bacterial signature of each individual. However, it could be related to the diet and in particular to the presence of dietary fibres (Cani et al, 2008). The gut bacteria from obese subjects are able to specifically increase the energy harvested from the diet, which provide an extra energy to the host. This conclusion was drawn from work showing that the axenic mice colonized with a conventional gut flora gain weight rapidly. The mechanisms of the apparent gain weight implied an increase in the intestinal glucose absorption, energy extraction from non-digestible food component (short chain fatty acids produced through the fermentation) and a concomitant higher glycemia and insulinemia, two key metabolic factors promoting lipogenesis. Thus an environmental factor such as gut microbiota regulates energy storage. The results, obtained both in rodents and human, suggest that obesity is associated with an altered composition of gut microbiota. However, this study did not demonstrate that the relative change in bacterial strains profile leads to different fates of body weight gain. This particularly original idea that the bacteria can contribute to the maintenance of the host body weight, is characterized by numerous paradoxes. It is not clear, however, whether the small increased of energy extraction can actually contribute to a meaningful body weight gain within a short period of time, as suggested in the gut flora transplantation studies. Moreover, other studies have clearly shown that a diet rich in non-digestible fibres decreases body weight, fat mass and the severity of diabetes (Cani et al, 2014). However these dietary fibres increase strains of bacteria able to digest these fibres and provide extra-energy for the host as they thus increase the total amount of bacteria in the colon (Kolida et al, 2013). This mechanism is not completely in accordance with the ‘‘energy harvesting theory’’ according to which the fermentation of non digestible polysaccharides would provide energy substrates for the host. In addition, it is difficult to conclude that small changes in energy ingestion (1–2%) can induce sufficient quick variation in weight (within two weeks) as observed in an American studies ( Backhed et aI, 2005). Importantly, the axenic mice colonized with the gut flora from normal mice ate more than their conventional mice counterparts; therefore, the body weight gain can also be dependent of the increased food intake. A last crucial point, which cannot depend only on the role played by the bacteria to harvest energy from nutrients escaping digestion in the upper part of the intestine, concerns a study showing that axenic mice are more resistant to diet-induced obesity. The authors maintained axenic or conventionalized mice on a high-fat/high-carbohydrates diet (western diet) and found that conventiona-lized animals fed the western diet gained significantly more weight and fat mass and had higher glycemia and insulinemia than the axenic mice. Strikingly, and opposite to the results previously observed in axenic mice fed a normal chow diet, the amount of western diet taken up by an axenic or a conventionalized mouse was similar and hence had similar fecal energy output. All those data suggest that a bacterially related factor is responsible for the development of diet-induced obesity and diabetes. GUT MICROBIOTA AND INFLAMMATION Obesity and type 2 diabetes are metabolic diseased characterized by a low grade inflammation (Wellen and Hotamisligil, 2011). In the models of high fat diet induced obesity, adipose depots express several inflammatory factors IL-1(interleukin-1), TNF-a (tumor necrosis factor-a) and IL-6 (interleukin-6) (Weisberg et al, 2010). These cytokines impaired insulin action and induce insulin resistance. For example, TNF-a phosphorylates serine residue substrate (IRS-1) from the insulin receptor leading its inactivation and it has been proposed that nutritional fatty acids trigger inflammatory response by acting via the toll-like receptor-4 (TLR4) signalling in the adipocytes and macrophages. It was shown that the capacity of fatty acids to induce inflammatory signalling following a high-fat diet feeding is blunted in the TLR4 knock out mice (Shi et al, 2014). TLR4 is the co-receptor for the lipopolysaccharides (LPS) constituent of the Gram negative bacteria. A triggering factor of the early development of metabolic diseases is the lipopolysaccharides, a molecule involved early in the cascade of inflammation. Furthermore, LPS is a strong inducer of inflammatory response and is involved in the release of several cytokines that are key factors triggering insulin resistance. The concept of dietary excess is more or less associated to high-fat feeding-induced inflammation. Experiment has shown that mice fed a high-fat diet for a short term period as two to four weeks exhibit a significant increase in plasma LPS. An endotoxemia that is characterized as a ‘‘metabolic endotoxemia’’, since, the LPS plasma concentrations were 10 to 50 times lower than those obtained during a septic shock. LPS is absorbed into intestinal capillaries to be transported by lipoproteins (i.e. chylomicrons). High-fat diet feeding changed gut microbiota in favour of an increase in the Gram negative to Gram positive. CD14 is a key molecule involved in the innate immune system is a multifunctional receptor constituted by a phosphatidyl inositol phosphate-anchored glycoprotein of 55 kDa expressed on the surface of monocytes, macrophages and neutrophils. CD14KO mice were hypersensitive to insulin even when fed a normal diet, suggesting that CD14 could be modulator of insulin sensitivity in physiological conditions. As a matter of fact, CD14KO mice resist high-fat diet and chronic LPS-induced metabolic disorders. Similarly hepatic steatosis, liver and adipose tissue inflammation and adipose tissue macrophages infiltration was totally blunted in the CD14KO mice fed a high-fat diet or bifidobacteria microflora Therefore high-fat feeding induced a low tone inflammation which originates from the intestinal absorption of the LPS. Thus data support the key idea that the gut microbiota can contribute to the pathophysiology of obesity and type 2 diabetes. High-fat feeding alters the intestinal microbiota composition were Bifidobacterium spp were reduced. Several studies have shown that this specific group of bacteria reduced the intestinal endotoxin levels and improved mucosal barrier function (Cani et al.,). The unique advantage of the prebiotic dietary fibres (oligofructose, [OFS])was used to specifically increase the gut bifidobacteria content of high fat diet treated mice. Among the different gut bacteria analysed, plasma LPS concentrations correlated negatively with Bifidobacterium spp. Together, these findings suggest that the gut microbiota contributes to the pathophysiological regulation of endotoxemia, and sets the tone of inflammation for the occurrence of diabetes/obesity. Thus, it would be useful to develop specific strategies for modifying gut microbiota to favour bifidobacteria growth and prevent the deleterious effect of high-fat diet-induced metabolic diseases (Cani et al.,2013). Figure 3: Signalling of LPs via NF-B and MAPK. ERK: extracellular signal related kinase, IL: Interleukin, IKB: Inhibitor of kappa B, IKK: IKB kinase, INOS: Inducible nitric oxide synthase, IRAK: Interleukin-1 receptor-associated kinase, JNK : c-jun NH2 –terminal kinase, LBP: Lipopolysaccharide binding protein, LPS: Lipopolysaccharide, MAPK: mitogen-activated protein kinase, MCP-1: monocyte chemotatic protein-1, MD-2: mycloid differentiation protein 2, MyD88: mycloid differentiation primary response gene 88, NF-KB: Nuclear factor Kappa B, NIK: NF-KB inducing kinase, TLR: toll-like receptor, TNF: tumor necrosis factor, TRAF6: TNF receptor-associated factor 6. Source: Boroni et al., 2014. MODULATION OF GUT MICROBIOTA The importance of gut microbiota in the mainte-nance of health has been receiving more attention worldwide. The homeostasis of gut microbiota depends on the characteristics of the host (age, gender, genetic factors) and the environment (stress, drugs, toxic agents, infections, diseases). However, the influ-ence of diet is also evident (Boroni Moreira et al., 2014). The conductance of future studies aiming to understand how changes in diet modulate gut microbiota composition is of great interest to help menu plannings that simulate the achievement of a favorable microbiota. Weight loss promotes changes in gut microbiota composition. .(Fleissner et al., 2015) The intake of specific dietary components (fatty acids, carbohydrates, micronutri-ents, prebiotics, probiotics) can result in changes in the composition of gut microbiota and modulate the expression of genes in the host, especially in organs as intestine, muscle, liver and adipose tissue (Boroni Moreira et al.2014,). The relevance of the use of prebiotics and probiotics in human’s obesity treatment is supported by few results obtained in interventional studies. However, animal models show potential beneficial effects. For example, genetically obese mice and mice fed with high-fat diet were given the prebiotic oligofructose. After the intervention it was observed a reduction in the circulatory levels of IL-18 and IL-1β. These cytokines are considered as gut microbial related immunologic factors that drive the obesity development.(Vijay-Kumar et al. 2014,). Amongst probiotics, Lactobacillus plantaraum shows a potential to modulate negative effects of high-fat diets. High dietary fat intake increased body weight gain, white adipose tissue weight, mean adipocyte size and serum total cholesterol and leptin concentrations, and decreased serum adiponectin concentration in mice. The administration of L. plantaraum to mice significantly reduced the mean adipocyte size and tended to reduce the white adipose tissue weight and serum total cholesterol and leptin concentrations as compared with the vehicle-administered mice. Thus, it is suggested that gut microbiota is an important and promising target for the treatment of obesity (Takemura et al.,2014). CONCLUSION Conventional thoughts regarding caloric intake,energy expenditure,and the development of diabetes,obesity and obesity-related complication are being challenged by recent revelation regarding the role of the gut microbiota, not only does this symbiotic relationship result in vast differences in nutrient acquisition and energy homeostasis, but it appears that diet composition can rapidly induce important changes in the microbiota, which in turn, result in further metabolic consequences for the host organism. REFERENCE Backhed, F., Ding ,H., Wang, T., Hooper, L.V., Koh, G.Y., and Nagy, A. (2004). The gut microbiota as an environment factor in regulation of fat storage. Proc Natl Academic Science. 101(44):15718-15723. Backhed, F., Ley, R.E., Sonnenburg, J.L., Peterson, D.A., and Gordon, J.I. (2005). Host bacterial mutualism in human intestine. Journal of Science. 307(5717):1915-1920. Blaut, M., and Klaus, S. (2012). Intestinal microbiota and obesity. Handbook of pharmacology.209:251-273. Boroni, A.P., Fiche, T.T., Gouveia, c., and Cassia, R.C. (2014). Gut microbiota and the development of obesity. Journal of Nutricion Hospitalaria. 27(5):1408-1414. Cani, P.D., Bibiconi,R., Knauf, C.,Waget, A., Neyrinck, A.M., Delzenne, N.M., Burcelin, R. (2015).Changes in gut microbiota control metabolic endotoxomia-inducer inflammation in high fat diet-induced obesity and diabetes in mice. Diabetes.57:1470-1481. Cani, P.D., Delzenne, N.M., Amar, J., and Burcelin, R.(2013). Role of gut microbiota in the development of obesity and insulin resistance following high-fat diet feeding. Pathologie Biologie. 56:305-309. Cani, P.D., Dewever, C., and Delzenne, N.M. (2014). Inulin-type fructans modulate gastrointestinal peptides involved in appetite regulation. British Journal ofNutrition .92(3:)521-526. Fleissner,C.K., Huebel, N., El-Bary, M.M.A., Loh,G., Klaus,S., and Blaut, M. (2015). Absence of intestinal microbiota does not protect mice from diet-induced obesity. British Journal of Nutrition. 104 (6):919-929. Hill, J.O. (2015). Understanding and addressing the epidemic of obesity: an energy balance prespective. Endo Rev Dec.27(7):750-761. Ji, B., and Nielsen, J. (2015). From next generation sequencing to systematic modeling of the gut microbiome. Front Genetics. 6:219-220. Kim, S.J., Choi, Y.H., and Pack, T. (2014). Obesity activates Toll-like receptor-mediated proinflammatory signaling cascades in the adipose tissue. Journal of Nutritional Biochemistry. 32:11-122. Kolida, S., Saulnier, D.M., and Gibson, G.R.(2013). Gastrointestinal microflora:Probiotics. Advanced Applied Microbiology.59:187-219. Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J.K., Knight, R. (2012).Diversity,stability and resilience of the human gut microbiota. Nature.489:220-230. Murri, M., Leiva, I., Gomez-Zumaquero, J.M., Tinahones, F.J., Cardona, F., Soriguer, F., and Queipo-Ortuno, M.I.(2013). Gut microbiota in children with type ! diabetes differ from that in healthy children, a case study control study. BMC Med.11:46-47. Othman, A.B., Mazin, A.Z., Ibrahim, T., and Mohammed, A. (2016). The role of Gut Microbiota in the development of obesity and diabetes. Biomed. Central.15:108-112. Qin J, Li Y, Cai Z, Li S, Zhu J, Zhang F, Liang S, Zhang W, Guan 1 Y, Shen D, et al. A metagenome-wide association study of gut microbiota in type2 diabetes. Nature. 2012;490:55-60. Rankinen, T., Zuberi, A., Chagnon, Y.C., Weisnagel, S. J., Argyropoulos, Walts, B., Perusse, and Bouchard, C. (2006).The human obesity gene map. Obesity.14:529-644. Shi, H., Kokoeva, M.V., Inouye,K., Tzameli, I, Yin, H., and Flier, J.S. (2014). TLR4 links innate immunity and fatty acid-induced insulin resistance. Journal of Clinical Investigation.116(11):3015-3025. Takemura, N., Okubo,T., and So/noyama, K.(2014). Lactobacillus plantarum strain reduces adipocyte sizein mice fed high-fat diet. Exp Biological Med.235(7):849-856. Tanaka, S., Kobayashi, T, Songjinda, P., Tatayema, A., Tsubouchi, M., Kiyohara, C., Shirakawa, T., and Nakajama, J.(2009). Influence of antibiotics exposure in the early postnatal period on the development of intestinal microbiota. FEMS Immunological Medical Microbiology.56:80-87. Vijay-Kumar, M., Aitken, J.D., Carvalho, F.A., Cullender, T.C., Mwangi, S., and Srinivasan, W.(2010). Metablic syndrome and altered gut microbiota in mice lacking Toll-like receptor 5 Science.328:228-231. Weisberg, S.P., McCann, D., Desai, M., Rosenbaum, M., Leibel, R.L., and Ferrante, A.W.(2010). Obesity is associated with macrophage accumulation in adipose tissue. Journal of Clinical Investigation.112(12):1796-1808. Zoetenda E.G and Vaughan E E. (2015). A microbial world within us. Journal of molecular microbiology. 59: 1639-1650 Qin. 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                                                                    SEMINAR PRESENTATION
ON
BCH 411
FRONTIERS IN BIOCHEMISTRY, MOLECULAR BIOLOGY AND BIOTECHNOLOGY
TOPIC:THE ROLE OF GUT MICROBIOTA IN THE DEVELOPMENT OF DIABETES AND OBESITY.
PRESENTED BY
OBINWA MARY-ANN UKAMAKA
REG NO: 2012474143
DEPARTMENT OF APPLIED BIOCHEMISTRY
FACULTY OF BIOSCIENCES
NNAMDI AZIKIWE UNIVERSITY,AWKA.
SUPERVISOR: MR.NWAJIOBI JIDE
DATE:DECEMBER, 2016 A

ABSTRACT
A recent growing number of evidences show that the increased prevalence of obesity and diabetes cannot be attributed to changes in the human genome, nutritional habits, or reduction in physical activity in our daily lives Gut microbiota may play an even an more important role in maintaining human health, as it function much like a “metabolic organ” influencing nutrient aquisition, energy homeostasis and, ultimately, the control of the body weight. Moreover, alterations in gut microbiota can lead to increase intestinal permeability, and metabolic endotoxemia which play a rolesss in the development of chronic low grade inflammatory state in the host that contributes to the development of obesity and diabetes. However the fact that gut microbiota can be modulated through dietary components highlights the importance to study how fatty acid, carbohydrates, probiotics, can influence gut microbiota composition and management of obesity. Gut microbiota seems to be an important and promising target in the prevention and treatment of obesity and its related metabolic disturbances.      




INTRODUCTION
The epidemics of obesity and type 2 diabetes mellitus in the past 20 years have led to numerous investigations concerning the mechanisms that are responsible for the development of these diseases.
The general view is that insulin resistance is an early alteration of type 2 diabetes mellitus and obesity, and both diseases are strongly influenced by genetics and environment. Moreover, studies in the past ten years have shown that low-grade inflammation has an important role in the molecular mechanism of insulin resistance in these diseases and more recently (within the past five years) a new component that has both genetic and environmental factors is also being studied: the gut microbiota.
This way, a paradigm has been dismantled: microorganisms should no longer be associated with pathogenesis, since both bacteria and their eukaryote hosts benefit from their cooperative relationships. In humans, there are at least 100 trillion microbial cells, collectively called microbiota, distributed in complex and site-specific communities. As the genome of these bacteria—the microbiome—contains hundreds of genes that do not exist in the human genome, we can consider our symbionts as an important extra organ.
This complex community—bacteria, eukaryotes, viruses and Archeae—in its majority cannot be cultured. The reasons for this limitation are unknown growth requirements of the bacteria, selectivity of the media that are used, stress imposed by the cultivation procedures, necessity of strictly anoxic conditions, and the difficulties on simulating the interactions of bacteria with other microbes and host cells. Thus, a new approach was introduced, culture-independent sequencing, which made detection of microbial genes and disease-associated patterns in our gut microbiota  possible. The bacterial component of the microbiota has been intensively studied in the past few years, including high-investment studies such as the Human Microbiome Project and MetaHIT.
Using this new approach made it possible to detect three dominating bacterial phyla in the human gastrointestinal tract: the gram-positive Firmicutes and Actinobacteria, and the gram-negative Bacteroidetes. Firmicutes is known as the largest bacterial phylum, comprehending 200 genera, which includes Lactobacillus, Mycoplasma, Bacillus, and Clostridium. In spite of Actinobacteria being also a dominant phylum, it is usually missed by RNA gene sequencing and can only be detected by fluorescent in situ hybridization.
Although gut microbiota has been described as relatively stable concerning its composition until old age, this temporal consistency considers that numerous variables are being held constant.
For example, dietary changes have been shown to have significant effects on the microbiota. Shifting mice to a high-fat, high-sugar ―Western‖ diet, from a low-fat, plant polysaccharide-rich diet, changed the microbiota within 24 hours . Likewise, shifting from a high-fat/low-fiber diet caused notable changes in the gut microbiota within a day.













ORIGIN AND COMPOSITION OF GUT MICRIBIOTA
The human body contains trillions of microorganisms that inhabit our bodies during and after birth.The gastrointestinal tract starts to be colonized during the delivery of the baby. During the first two years of life de microbiota is unstable and less diverse than in the adulthood, when the complexity and diver-sity is higher. 5 Many external factors influence the composition of the microbiota, especially the diet, the hygiene conditions and the use of antibiotics. 6ing the pregnancy, infant’s intestinal tract is free of mi-crobes until exposed to maternal vaginal microbes during normal birth. Infants born through Caesarian section are exposed to maternal skin bacteria altering their bacterial gut composition. Feeding represents another source of microorganisms where breast fed babies have different gut microbiota composition than formula fed babies(Tanaka et al.,2009). Introduction of solid food represents another shift in the composition of babies gut microbiota.
After that, gut microbiota remains relatively unchanged until old age where the composition changes again. Adulthumans have more than 10 times the number of bacterial cells than the cells constituting the human body. Majority of microbiota in the GI tract are bacteria, nevertheless, viruses fungi and other microorganisms are still present. Even though, individuals have unique microbiota composition, gut microbiota is mainly members of four phyla (Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria) ,The distribution of microorganisms throughout the gastrointestinal tract is not homogenous. The stressful environment (gastric juice, bile, pancreatic juice, peri-stalsis) in the stomach and small intestine limits bacte-rial growth and the number of microorganisms.The large intestine contains the highest number of bacteria con-taining over 10 11 bacteria per gram of intestinal con-tent. The mouth contains 10 12 followed by the Ileum containing 10 8 –10 9 bacterial. On the other hand, the jejunum harbors 10 5 –10 6 while the stomach has the least number of bacteria 10 3 –10 4(Othman et al.,2016). The gut microbiota plays different roles that are important for the host. They exert a trophic effect in the intestinal epithelium, favoring the development of the microvilli, which in turn favors the absorption of nutri-ents. The influence of microbiota in innate and adaptive immune system maturation contributes to systemic and local immune homeostasis and immune tolerance for a variety of antigens. The modulation of the immune system activity can influence the intestinal barrier func-tion. The capacity to break down non-digested dietary molecules into metabolites such as short chain fatty acids (SCFS) and to synthesize vitamins demonstrates their importance to human nutrition.
Even though we are still far from identifying, let alone characterizing all bacteria in our system, advancing molecular biology techniques such as next-generation sequencing has tremendously contributed to our understanding of the gut microbiota(Ji and Nielsen.,2015). The use of gnotobiological methods to breed mice in a sterile environment provided an invaluable tool to understand the role of infecting con-trolled bacterial cultures and defined bacterial strains into animals. Studying their effect through various genomic and proteomic tools.










DIABETES AND GUT MICROBIOTA

It’s becoming increasingly evident that gut microbiota is contributing to many human diseases including diabetes both type 1 and type 2. Type 1 diabetes (T1D) is an autoimmune disease that is caused by the destruction of pancreatic β-cells by the immune system. Even though T1D is mainly caused by genetic defect, epigenetic and environmental factors have been shown to play an im-portant role in this disease. Higher rates of T1D inci-dence have been reported in recent years that are not explained by genetic factors and have been attributed to changes in our lifestyle such diet, hygiene, and antibiotic usage that can directly affect microbiota. It has been shown that diabetes incidence in the germ free non-obese diabetic subjects or patients (NOD) was significantly increased which is in line with the observa-tion that the rates of T1D is higher in countries with stringent hygiene practices (Guiden et al.,2015). Similarly comparison of the gut microbiota composition between children with high genetic risk for T1D and their age mhealthy controls showed less diverse and less dynamic microbiota in the risk group. In the Diabetes Pre-vention and Prediction (DIPP) study it was shown that new-onset T1D subjects had different gut microbiota composition than controls(Murri et al., 2013).They showed that in the control group, mucin synthesis was induced by lactate- and butyrate-producing bacteria to maintain gut integrity while mucin synthesis was prevented by the non-butyrate-producing lactate-utilizing bacteria leading to β-cell autoimmunity and T1D (Othman et al.,2016).

Recently, research has pointed out that the intestinal microbiome might be an important contributor for the development of type 2 diabetes (T2D). The use of genome-wide association studies (GWAS) has achieved many elucidations in this matter(Qin et al.,2013). characterized the gut microbiota of T2D patients and observed increase in membrane transport of sugars, branched-chain aminoacids transport, methane metabolism, xenobiotics degradation, and sulphate reduction. However, they observed decrease in the levels of butyrate biosynthesis, bacterial chemotaxis, flagellar assembly, vitamins and cofactors metabolism. This study has also shown that the gut environment of T2D individuals is one that stimulates bacterial defense mechanisms against oxidative stress and against drugs.
(Andrea and Mario, 2013)



GUT MICROBIOTA  AND ITS ROLE IN ENERGY  HOMEOSTASIS  AND THE DEVELOPMENT OF OBESITY
The metabolic activities of the gut microbiota have the end results of extracting calories from ingested dietary substances, helping to store those calories in host adipose tissue for later use, and providing energy and nutrients for microbial growth and proliferation. Bäckhed et al 1 dem-onstrated that conventionally raised mice have a 40% higher body fat content and 47% higher gonadal fat con-tent than germ-free (GF) mice, despite lower food intake (Frazier et al 2011).
However, it has been suggested that the main routes under influence of gut microbiota that could contribute to obesity develop-ment are provision of extra calories, increased lipopro-tein lipase (LPL) activity, lipogenesis, increased intestinal permeability, endotoxemia and endocannabi-noid (eCB) system (Blaut and Klaus, 2012).Gut microbiota contribute to energy metabolism through the production of SCFA that are produced by colonic fermentation which involves the anaerobic breakdown of dietary fiber, protein and peptides . The most important SCFA produced are acetate, propionate and butyrate. Acetate and propionate are mostly produced by Bacteriodetes phylum while butyrate is produced by the Firmicutes phylum (Othman et all 2016). These SCFA can provide additional calories when they are oxidized by the host, favoring the higher weight and fat gain observed in these animals. In addition, the binding of SCFA to G protein-coupled receptor (GPR) in the intestine induces the secretion of the hormone peptide YY (PYY). This hormone reduces intestinal transit time, increasing the time for nutrient absorption from the intestinal lumen. In fact, obese and overweight subjects presented higher concentration of SCFA in their feces in comparison to lean individuals (Bodoni et al, 2014).
Low grade inflammation is a hallmark of obesity. Production of pro- inflammatory cytokines are coordinated via the Toll- like receptors and the master regulator of of key inflammation cascades the nuclear factor kappa(NF-kB) (Kim et al, 2012).
The LPL (lipopolysaccharide) activity influences the accumulation of triglycerides in the adipose tissue. The microbiota can affect the activity of this enzyme by the influence on the expression of the protein fasting-induced adipose factor (FIAF). In the absence of microbiota (germ-free mice) it is observed higher expressin of FIAF. 16 On the other hand, the conventionalization of the germ-free animal causes inhibition of the expression of the FIAF and also stimulates body fat gain. It is suggested that FIAF is a circulating inhibitor of LPL activity. Thus, the inhibition of FIAF expression by the presence of microbiota allowus higher activity of LPL and accumulation of triglycerides in adipocytes (Backhad et al, 2004).
Figure 2:  Alteration in gut microbiota composition due to obesity is accompanied by changes in activation of enzymes and pathways which leads to and increased inflammatory state and energy harvest.
AMPK: AMP- activated kinase, SCFA: Short chain fatty acids, LPL: Lipoprotein lipase, ACC: acetyl- CoA carboxylase, CPT1: Carnitine palmitoyltransferase.
Source: Andrea and Mario., 2013
THE EFFECT OF GUT MICROBIOTA ON ENERGY METABOLISM
The biological functions controlled by the intestinal flora are related to the effectiveness of energy harvest, by the bacteria, of the energy ingested but not digested by the host. Among the dietary compound escaping to the digestion occurring in the upper part of the human gastro-intestinal tract, the polysaccharides constitute the major source of nutrient for the bacteria. Part of these polysaccharides could be transformed into digestible substances such as sugars, or short chain carboxylic acids, providing energy substrates which can be used by the bacteria or the host. The control of body weight depends on mechanisms subtly controlled over time and a small daily excess, as low as 1% of the daily energy needs, can have important consequences in the long term on body weight and metabolism (Hill, 2015). Consequently, the gut microbiota of obese subjects changed according to the loss of body weight occurring after a hypocaloric diet. It was demonstrated that two groups of bacteria are dominant in the intestinal tract, Bacteroidetes and Firmicutes (Cani et al, 2008). The quantification and characterization of each dominant group of bacteria were carried out by measuring the concentration of the bacterial 16S rRNA. The number of Bacteroidetes bacteria depended on the weight loss whereas the Firmicutes bacteria group remained unchanged. Importantly, the bacterial lineage was constant one year after the dietary intervention for a given body weight, validating the bacterial signature of each individual. However, it could be related to the diet and in particular to the presence of dietary fibres (Cani et al, 2008).
 The gut bacteria from obese subjects are able to specifically increase the energy harvested from the diet, which provide an extra energy to the host. This conclusion was drawn from work showing that the axenic mice colonized with a conventional gut flora gain weight rapidly. The mechanisms of the apparent gain weight implied an increase in the intestinal glucose absorption, energy extraction from non-digestible food component (short chain fatty acids produced through the fermentation) and a concomitant higher glycemia and insulinemia, two key metabolic factors promoting lipogenesis. Thus an environmental factor such as gut microbiota regulates energy storage. The results, obtained both in rodents and human, suggest that obesity is associated with an altered composition of gut microbiota. However, this study did not demonstrate that the relative change in bacterial strains profile leads to different fates of body weight gain.
This particularly original idea that the bacteria can contribute to the maintenance of the host body weight, is characterized by numerous paradoxes. It is not clear, however, whether the small increased of energy extraction can actually contribute to a meaningful body weight gain within a short period of time, as suggested in the gut flora transplantation studies. Moreover, other studies have clearly shown that a diet rich in non-digestible fibres decreases body weight, fat mass and the severity of diabetes (Cani et al, 2014). However these dietary fibres increase strains of bacteria able to digest these fibres and provide extra-energy for the host as they thus increase the total amount of bacteria in the colon (Kolida et al, 2013). This mechanism is not completely in accordance with the ‘‘energy harvesting theory’’ according to which the fermentation of non digestible polysaccharides would provide energy substrates for the host.
In addition, it is difficult to conclude that small changes in energy ingestion (1–2%) can induce sufficient quick variation in weight (within two weeks) as observed in an American studies ( Backhed et aI, 2005). Importantly, the axenic mice colonized with the gut flora from normal mice ate more than their conventional mice counterparts; therefore, the body weight gain can also be dependent of the increased food intake. A last crucial point, which cannot depend only on the role played by the bacteria to harvest energy from nutrients escaping digestion in the upper part of the intestine, concerns a study showing that axenic mice are more resistant to diet-induced obesity. The authors maintained axenic or conventionalized mice on a high-fat/high-carbohydrates diet (western diet) and found that conventiona-lized animals fed the western diet gained significantly more weight and fat mass and had higher glycemia and insulinemia than the axenic mice. Strikingly, and opposite to the results previously observed in axenic mice fed a normal chow diet, the amount of western diet taken up by an axenic or a conventionalized mouse was similar and hence had similar fecal energy output. All those data suggest that a bacterially related factor is responsible for the development of diet-induced obesity and diabetes.
GUT MICROBIOTA AND INFLAMMATION

Obesity and type 2 diabetes are metabolic diseased characterized by a low grade inflammation (Wellen and Hotamisligil, 2011). In the models of high fat diet induced obesity, adipose depots express several inflammatory factors IL-1(interleukin-1), TNF-a (tumor necrosis factor-a) and IL-6 (interleukin-6) (Weisberg et al, 2010). These cytokines impaired insulin action and induce insulin resistance. For example, TNF-a phosphorylates serine residue substrate (IRS-1) from the insulin receptor leading its inactivation and it has been proposed that nutritional fatty acids trigger inflammatory response by acting via the toll-like receptor-4 (TLR4) signalling in the adipocytes and macrophages. It was shown that the capacity of fatty acids to induce inflammatory signalling following a high-fat diet feeding is blunted in the TLR4 knock out mice (Shi et al, 2014). TLR4 is the co-receptor for the lipopolysaccharides (LPS) constituent of the Gram negative bacteria.  A triggering factor of the early development of metabolic diseases is the lipopolysaccharides, a molecule involved early in the cascade of inflammation. Furthermore, LPS is a strong inducer of inflammatory response and is involved in the release of several cytokines that are key factors triggering insulin resistance. The concept of dietary excess is more or less associated to high-fat feeding-induced inflammation. Experiment has shown that mice fed a high-fat diet for a short term period as two to four weeks exhibit a significant increase in plasma LPS. An endotoxemia that is characterized as a ‘‘metabolic endotoxemia’’, since, the LPS plasma concentrations were 10 to 50 times lower than those obtained during a septic shock. LPS is absorbed into intestinal capillaries to be transported by lipoproteins (i.e. chylomicrons). High-fat diet feeding changed gut microbiota in favour of an increase in the Gram negative to Gram positive. CD14 is a key molecule involved in the innate immune system is a multifunctional receptor constituted by a phosphatidyl inositol phosphate-anchored glycoprotein of 55 kDa expressed on the surface of monocytes, macrophages and neutrophils.
CD14KO mice were hypersensitive to insulin even when fed a normal diet, suggesting that CD14 could be modulator of insulin sensitivity in physiological conditions. As a matter of fact, CD14KO mice resist high-fat diet and chronic LPS-induced metabolic disorders. Similarly hepatic steatosis, liver and adipose tissue inflammation and adipose tissue macrophages infiltration was totally blunted in the CD14KO mice fed a high-fat diet or bifidobacteria microflora
Therefore high-fat feeding induced a low tone inflammation which originates from the intestinal absorption of the LPS.
Thus data support the key idea that the gut microbiota can contribute to the pathophysiology of obesity and type 2 diabetes. High-fat feeding alters the intestinal microbiota composition were Bifidobacterium spp were reduced. Several studies have shown that this specific group of bacteria reduced the intestinal endotoxin levels and improved mucosal barrier function (Cani et al.,). The unique advantage of the prebiotic dietary fibres (oligofructose, [OFS])was used to specifically increase the gut bifidobacteria content of high fat diet treated mice. Among the different gut bacteria analysed, plasma LPS concentrations correlated negatively with Bifidobacterium spp. Together, these findings suggest that the gut microbiota contributes to the pathophysiological regulation of endotoxemia, and sets the tone of inflammation for the occurrence of diabetes/obesity. Thus, it would be useful to develop specific strategies for modifying gut microbiota to favour bifidobacteria growth and prevent the deleterious effect of high-fat diet-induced metabolic diseases (Cani et al.,2013).
Figure 3: Signalling of LPs via NF-B and MAPK. ERK: extracellular signal related kinase, IL: Interleukin, IKB: Inhibitor of kappa B, IKK: IKB kinase, INOS: Inducible nitric oxide synthase, IRAK: Interleukin-1 receptor-associated kinase, JNK : c-jun NH2 –terminal kinase, LBP: Lipopolysaccharide binding protein, LPS: Lipopolysaccharide, MAPK: mitogen-activated protein kinase, MCP-1: monocyte chemotatic protein-1, MD-2: mycloid differentiation protein 2, MyD88: mycloid differentiation  primary  response gene 88, NF-KB: Nuclear factor Kappa B, NIK: NF-KB inducing kinase, TLR: toll-like receptor, TNF: tumor necrosis factor, TRAF6: TNF receptor-associated factor 6.
Source: Boroni et al., 2014.


MODULATION OF GUT MICROBIOTA
The importance of gut microbiota in the mainte-nance of health has been receiving more attention worldwide. The homeostasis of gut microbiota  depends on the characteristics of the host (age, gender, genetic factors) and the environment (stress, drugs, toxic agents, infections, diseases). However, the influ-ence of diet is also evident (Boroni Moreira et al., 2014). The conductance of future studies aiming to understand how changes in diet modulate gut microbiota composition is of great interest to help menu plannings that simulate the achievement of a favorable microbiota.
Weight loss promotes changes in gut microbiota composition. .(Fleissner et al., 2015) The intake of specific dietary components (fatty acids, carbohydrates, micronutri-ents, prebiotics, probiotics) can result in changes in the composition of gut microbiota and modulate the expression of genes in the host, especially in organs as intestine, muscle, liver and adipose tissue (Boroni Moreira et al.2014,).
The relevance of the use of prebiotics and probiotics in human’s obesity treatment is supported by few results obtained in interventional studies. However, animal models show potential beneficial effects. For example, genetically obese mice and mice fed with high-fat diet were given the prebiotic oligofructose. After the intervention it was observed a reduction in the circulatory levels of IL-18 and IL-1β. These cytokines are considered as gut microbial related immunologic factors that drive the obesity development.(Vijay-Kumar et al. 2014,).
Amongst probiotics, Lactobacillus plantaraum shows a potential to modulate negative effects of high-fat diets. High dietary fat intake increased body weight gain, white adipose tissue weight, mean adipocyte size and serum total cholesterol and leptin concentrations, and decreased serum adiponectin concentration in mice. The administration of L. plantaraum to mice significantly reduced the mean adipocyte size and tended to reduce the white adipose tissue weight and serum total cholesterol and leptin concentrations as compared with the vehicle-administered mice. Thus, it is suggested that gut
microbiota is an important and promising target for the treatment of obesity (Takemura et al.,2014).







CONCLUSION
Conventional thoughts regarding caloric intake,energy expenditure,and the development of diabetes,obesity and obesity-related complication are being challenged by recent revelation regarding the role of the gut microbiota,  not only does this symbiotic relationship result in vast differences in nutrient acquisition and energy homeostasis, but it appears that diet composition can rapidly induce important changes in the microbiota, which in turn, result in further metabolic consequences for the host organism.








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logophoricity is functional both in Issele Mkpitime and Standard Igbo.




ABSTRACT
 The main focus of this research work is to comparatively study and analyse logophoricity in Issele Mpkitime dialect of Igbo and standard Igbo in order to make a comparative study and analysis of logophoricity betweenthe two. The primary linguistic data was gotten through elicitation method.  In summary, logophoricity in Issele Mkpitime and standard Igbo are the same because they exist in the same way. This means that  logophoricity is functional both in Issele Mkpitime and Standard Igbo.




















 INTRODUCTION
The research was done to study the existence and use of logophoricity in Issele Mkpitime dialect of Igbo .According to Curnow (2002), Hagege introduced logophor to show special pronominal forms. Logophors are referred to with logophoric pronoun. There is a difference between ordinary pronoun and logophoric pronoun. Logophoric pronoun is used to refer to distinct forms of pronoun. Some languages use reflexive pronoun to show logophoricity, others us a special class of pronoun. Logophors are used in a discourse to lay emphasison the person whose thought or perception is reported. Pronoun  for example, you ,I , me, and others are different from logoghoric  pronouns because they replace noun. When they  function as logophoric trigger in a logophoric domain, they are called logophors it can be called logophoric  pronoun or logophors.















LITERATURE REVIEW
 INTRODUCTION
The literature review is on logophoricity. In this section logophoricity will be discussed based on theoretical review, empirical review and theoretical framework, then summary and conclusion.

THEORETICAL REVIEW
Many authors have worked on logophoricity in many languages and many definitions has also been given. According to timothy J. Curnow, the term logophoric was introduced by Hagege (1974) to refer to special pronominal forms found in West Africa. Schlenker (1999, 2003) points out that logophors can be considered instances of secondary indexicals in reported speech. Oliver (2004) sees logophoric pronouns as that which refers to the person (in the matrix clause) whose speech thoughts or knowledge is being reported.Culy(1997) cited in Oliver (2004) gave an additional information by saying that logophoric pronoun occurs in the complement of a speech predicate.For instance;
IM:  O          siri     na      ya     bia.
 GL: 3PGS     said   DET   LOG  came.
       He said that he came.
In the above example, the word marked LOG is the logophoric pronoun that is the person whose speech is being reported. The logophoric pronoun is in the predicate position and it comfirmed what Culy cited in Iliver’s work said.
In 1994, Culy gave a hierarchical order of logophoric lincersers based on 32 languages: speech – thought -  knowledge – direct perception. He gave the environments for LOG marking  which includes;



SPEECH PREDICATE: Say, ask, tell (write)
REPORTED SPEECH: Know.
THOUGHT: Thinks, understands, forget, remember.
EMOTION:Anger, fear, happiness,
DIRECT PERCEPTIONS: See.
According  to crystal(2008), a logophoric pronoun refers to a person whose speech or thought is represented in discourse. Self forms , according to Reinhart and Reuland (1991, 1993) can also be seen as logophors. Logophoric self-forms is used to refer to an assigned epistemic validator. (Stirling 1993) . It refers to an entity that takes responsibility for the ascription of truth values to propositions in a given discourse segment.
Summarily, the definitions given is talking about indexicals. Logophors are used to lay emphasis on the person whose speech is reported and not on the person reporting. This is usually done with  distinct pronouns. It can be called Logophors, logophoricity, or logophoric pronouns. Logophors can be seen in context of verbs of speaking,thinking et cetra and it is usually seen in predicate not the subject position. The definitions of logophoricity has been expanded over the years with scholars distinguishing between logophoric pronouns and verbal logoporicity. It is used either with the third person or with the third person and second person and they appear obligatorily. Types of  verbal include; logophoric cross-referencing: logophoric cross-reference languages have an additional verbal form or forms specially marking logophoricity. Logophoric first person marking: Here a verbal inflection on the surbodinate verb shows that the subject is first person. It can be found in singular and plural referents. Logophoric verbal affixes:it is the least common. Here verbal affixes are attached to words to show coreference  of some subordinate argument of matrix clause. of speech or thought.
I prefer Tatiana’s definition of logophoric pronouns because it is easily understood. It is something we see in our everyday life. With her definitionsyou can easily find the logohors in the discourse. The definitions of logophoricity by different authors have been given and also the explanations of definitions and types of logophoricity was discussed. Her work on logophricity is more preferred definition of logophoricity.



EMPIRICAL REVIEW
In Oliver’s work on logophoricity, he gave some terminologies that will help people understand logophoricity better. They include;
1. Logophoric trigger: The person whose speech or thoughts is reported.
2. Logophoric domain:The stretch of discourse in which the speakers thought or perception is    reported.
3.Sentential logophoric domain: clause subordinate to the one in which the trigger is identified.
4. Discourse logophoric domain : May extend across several utterances.
5. Logophoric target: Any element in the matrix clause that is co referent with the trigger.
 For instance; SI:    O        siri     na       ya       dara.
                       GL: 3PSG   said   DET   LOG    fall.
                                He said that he fell.
In example above, ‘ya’ is the logophoric  trigger, the whole of the sentence or the period when the report was made is the logophoric domain and the logophoric  target is ‘o’  because he is the person that is co referent to the trigger.
Also Comrie(19983) discussed logophoricity based on young switch reference system.or logophoric reference. He outlined what switch reference is all about, they include the following.
1.      Switch reference system are marked as an inflectional category on the verb of the independent( embedded clause).
2.      It is used with all person or number variants.
3.      It is primarily concerned with grammatical subjects.
4.       Co referents are overtly marked or if only one , it is the different subject form.
In this work , Olivers work will be used to throw more light on logophoricity. In the data, the logophoric trigger, domain and target will be shown because I see it as the more basic terms.It can be found easily in many languages when compared to switch reference approach. Oliver and Comrie’s works on logophoricity when compared with Comrie’s work is considered more acceptable.

THEORETICAL FRAMEWORK
The descriptive method will be used to analyse the data collected.

SUMMARY AND CONCLUSION.
In this section, the definitions , types, works of scholars, theoretical framework were discussed under theoretical , empirical, and theoretical framework. The chosen works will be applied in the next chapter.

DATA  PRESENTATION AND ANALYSIS
1.      SI  : siri na ya biara
IM  : siri na  ya          bia.
GL:  3PSG Said DETLOG came
          ENG :He said that he came ( Hyman and Comrie 1981)
2          SI:si a gaba.
            IM : sia ya nama.
            GL: 3PSG  Said  LOG go.
          ENG :He said he should go (Hedinger 1984:95)
3         SI: siri ya biara n’tta
           IM: si na ya bia n’           tta.
           GL: 3 PSG    said DET LOG come PREP morning
           ENG : He said that he came this morning (Anderson and Goyvaerts 1986:313)



4        SI:Umuaka siri na bu l ha
          IM :Umundi asi na ha nwel af
          GL:Children said DET LOG own house  DET.
          ENG:Children said that it was their house
5         SI :Kofi si na pr
           IM:Kofi asi na pga
           GL: Kofi said DET LOG go
           ENG: Kofi said that he left (clements 1975:142)
6          SI : siri na ya dara
           IM : si na ya dahi.
           GL: 3PSG Said DET LOG fall
           ENG He said that he fell.
7         SI: Lebare siri na ya tiri ya ihe.
           IM Lebare siri na ya tia ife
           GL Lebare said DET LOG beat him thing.
            ENG Lebare said that he beat him
8          SI :Anr m n’ on Emeka na dara
            IM :  An m n ‘       on Emeka       na       ya da
             GL:IPS heard PREP mouth Emeka DET LOG fall.
               I heard from Emeka that he fell



9          SI: O were iwena ya dara.
            IM:  O were      iwe       na ya dara.
            GL: IPSG  became   angry  DET    LOG   fall.
             He became angry that he fell.
10. SI: O kpesara na onweghi ihe ya nwere.
     IM: O           kpesara    na         onweghi    ihe      ya     nwere.
     GL: 3PSG   complain DET      does not   thing   LOG   have.
            She complains that she has nothing.
11. SI: Osaro siri na ya zuru ji ahu.
     IM: Osaro    siri     na          ya       zuru     ji       ahu.
    GL: Osaro    said    DET     LOG    stole   yam  DET.
           Osaro said he stole the yam.
12. SI: Umuaka    siri    na      ha       riri     ji.
      IM: Umundu    siri      na     fa        riri     ji     ahu.
      GL: Umundu  said   DET  LOG    ate   yam  DET.
           Children said that they ate yam.
13. SI: nyaah, siri na ya  ga abia taa.
       IM:     siri  nyaah na ya ga-abia taa.
       GL: He  said   yesterday  DET  LOG  will come    today.
             Yesterday, he said that he is going to come today



14. SI: siri na ya gafere gba.
     IM:      si       na       ya       gafe       kitaa.
     GL: He   said   DET   LOG    passed    now.
           He said that he passed now.
15. SI: Nwunye siri na ya ghotara.
     IM: Nwunye  si     na       ya     awoghana.
     GL: Wife     said  DET  LOG    understood.
             Wife said that she understood.
16. SI: muaka ahu siri na o bu ulo ha.
     IM: muaka     af    asi     na       ha     onwe   ulo      afu.
     GL: Children   DET   said  DET   LOG   own    house   DET.
          Children said it is their house.
17. SI: gwara m na nwanne nne ya nke nwoke anwụọla.
      IM: gwaram na nwanne nne ya nke nwoke anwụọla.
      GL: 3PSG    told       me   DET   sibling   mother LOG    of       man       died.
        He told me that his uncle has died.
18.  SI: siri bia saa m.
      IM:          siri     m    bia     wua.
      GL:3PSG   said   me  come  wash.
           She said come and wash me.



19.SI: Oumar  gwaram m na ya puru na ejighi akpa.
    IM: Oumar    gwaram   m      na       ya     pizi   na ojini    akpa.
    GL: Oumar      told       me   DET   LOG  left   without      bag.
       He told me that he left without a bag
20. SI:   si na ya gaba.
      IM:           si     na        ya      nama.
      GL: 3PSG   said  DET   LOG       go.
             She said that he should go.

DATA ANALYSIS.
Logophoricity is used in Issele  Mkpitime  the same way it is used in Igbo . it is used in the context of verbs of speaking to indicate the interest of the person whose speech, thoughts or perceptions are reported. the  words marked LOG are the logophors or  logophoric pronouns in the data. They can also be called Logophoric triggers which are the ones whose thoughts , perceptions or knowledge is being reported. There is a little difference morphologically, the pronoun ‘ha’ in standard Igbo is written as ‘fa’in Issele Mkpitime dialect of Igbo. The pronouns in the sentences are logophoric trigger and their co- referents  are the logophoric target. Thelogophoric domain is the period when the various reports or conversations were made.







SUMMARY AND CONCLUSION
There is existence of logopophoricity in Issele Mkpitime dialect of Igbo  and logophoricity is used the same way in both standard Igbo and Issele Mkpitime  dialect of Igbo. Logophoric pronouns is used to lay emphasis on the person whose speech or thought is reported, by this i mean that they are used in context of verb of speaking to indicate theperson whose speech, knowledge or thought is reported.



















REFERENCES
Hagege C. 1974. Les Pronoms logophoriques.In Tatiiana Nikitina. 2012. Logophoric discourse and first personin wan (West Africa) . Anthropologocal Linguistics. Vol 54, num3,fall 2012. Pp 280-301. Nebraska press.
David Crystal .2008. A dictionary of linguistics and phonology. 6th ed. Oxford: Blackwell.
Timothy Curnow. 2002. Proceedings of 2002 conference of Australian Linguisti Society: Three types of verbal logophoricity in African languages.vol 31, no 1and 2.University of new south wales.
Oliver Bond.2004. A broader perspective on logophoricity: beyond point of view in Ogonoid languages. ACAL 35 DU Bois Institution, Harvard University.
Peter Collin and Megiste Amberber.2003. Studies in African linguistics. Vol 31, no 1 and 2. University of new south wales.