Browsing by Subject "Darmbakterien"

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Characterization of dietary and genetic influences on the gastrointestinal microbiota
(2023) Bubeck, Alena Marie; Fricke, Florian W.
Although the gut microbiota is known to contribute fundamentally to human health, e.g. by promoting the maturation of the immune system and intestinal homeostasis, the factors shaping its composition are only poorly understood. Extrinsic and intrinsic influences can disturb the tightly controlled equilibrium between the microbiome and the host and induce dysbiosis, which has been linked to diverse health conditions such as obesity, atherosclerotic cardiovascular disease (ACVD) and inflammatory bowel disease (IBD). Therefore, understanding events leading to microbial perturbations and the prediction of associated health outcomes could aid in the prevention and treatment of these conditions. In this work, the impact of dietary and genetic factors on gastrointestinal microbiota compositions were determined, with the diet serving as an exemplary extrinsic, modifiable microbiota-relevant factor and with a genetic deficiency in a mouse model for intestinal inflammation serving as an exemplary intrinsic, non-modifiable microbiota-relevant factor. In both studies, microbial communities obtained from either a human or a murine cohort, respectively, were taxonomically characterized by 16S rRNA gene amplicon sequencing and analyzed in the context of metabolic and inflammatory implications for the host. In ACVD, the reduction of excess blood cholesterol, which is a main risk factor, is tackled by clinical interventions aiming to reduce cholesterol uptake from exogenous, dietary sources or by inhibiting endogenous cholesterol biosynthesis. Cholesterol-to-coprostanol conversion by the intestinal microbiota has also been suggested to reduce intestinal and serum cholesterol availability, but the dependencies of cholesterol conversion on specific bacterial taxa and dietary habits, as well as its association with serum lipid levels remain largely unknown. To study microbiota contributions to human cholesterol metabolism under varying conditions, fecal microbiota and lipid profiles, as well as serum lipid biomarkers, were determined in two independent human cohorts, including individuals with (CARBFUNC study) and without obesity (KETO study) on very low-carbohydrate high-fat diets (LCHF) for three to six months and six weeks, respectively. Across these two geographically independent studies, conserved distributions of cholesterol high and low-converter types were measured. Also, cholesterol conversion was most dominantly linked to the relative abundance of the cholesterol-converting bacterial species Eubacterium coprostanoligenes, which was further increased in low-converters by LCHF diets, shifting them towards a high-conversion state. Lean cholesterol high-converters, which were characterized by adverse serum lipid profiles even before the LCHF diet, responded to the intervention with increased LDL-C, independently of fat, cholesterol and saturated fatty acid intake. These findings identify the cholesterol high-converter type as a potential predictive biomarker for an increased LDL-C response to LCHF diet in metabolically healthy lean individuals. Although the etiology of IBD has not been fully resolved, an interplay between the intestinal microbiota, environmental factors and an individual’s genetic susceptibility is thought to trigger chronic inflammation by a dysregulation of the immune response in the gut. To identify colitis-associated microbiota alterations throughout the development of spontaneous colitis, mice with a genetic deficiency of the anti-inflammatory cytokine Interleukin-10 (IL-10) from different litters were co-housed with wild-type mice and monitored for 20 weeks. The scoring of mice based on their phenotype and stool consistency mirrored the state of mucosal inflammation as assessed based on histopathological examinations and cytokine expression profiles. Also, the state of colitis was characterized by global microbiota alterations and susceptibility to colitis was dependent on litter-specific microbiome compositions that mice adopted early on in their lives. Colitis development was further associated with the presence of the bacterial genus Akkermansia in mature mice shortly before symptoms manifested. This genus was also a good predictor of colitis-related mice withdrawal, suggesting the potential of Akkermansia to serve as an early onset, subclinical colitis marker. In summary, fecal microbiota characterizations in response to LCHF diets in humans and throughout the development of intestinal inflammation in a colitis mouse model highlight the potential of personalized microbiome-based patient classifications to predict clinical outcomes and improve treatment approaches.
Comprehensive characterization of microbiota in the gastrointestinal tract of quails and two high yielding laying hen breeds
(2023) Roth, Christoph Florian; Camarinha-Silva, Amélia
The microbiomes composition in the gastrointestinal tract (GIT) is subject to several changes and influences. In addition to breed, sex, or diet, age affects the GIT microbiome dynamics of laying hens and quails. From the first day, the microbiome develops and increases its bacterial load to thousands of species. Then, depending on the diet fed, the animals microbiome and associated active bacteria vary and directly influence the animals nutrient uptake and efficiency. Omics technologies give insights into changes in microbes in the GIT (crop, gizzard, duodenum, ileum, caeca). In addition, they can reveal how feed supplements such as calcium (Ca) or phosphorus (P) can affect host health and performance through alterations in the microbiome. The Japanese quail has been an established animal model for nutritional and biological studies in poultry for the last 60 years. In particular, its short development time makes it a convenient model for microbiome research. However, compared to broiler microbiome research, the quail microbiome is still poorly understood. Animals of the breed Coturnix japonica were housed under the same conditions, fed a diet with P below recommendation, and the ileum microbiota characterized. Microbiota relations with gender and higher or lower predisposition of the birds for PU, CaU, FI, BWG, and FC were described (Chapter II). In addition, these performance parameters influenced the relative average abundance of bacteria like Candidatus Arthromitus, Bacillus, and Leuconostoc. Gender affects specific bacterial groups of the GIT, such as Lactobacillus, Streptococcus, Escherichia, and Clostridium, which differ in average abundance between male and female quails. Despite the comprehensive microbiota analysis, the interplay between animal genetics, diet, sex, and microbiome functionality is not yet understood. The laying hen breeds Lohmann LSL-Classic and Lohmann Brown-Classic are used worldwide. Little is known about the interaction with microbiome composition, performance, dietary effects, and changes during the productive life that might help develop feeding strategies and microbiome responses on a large scale. Because of the importance of P and Ca in poultry diet, the research in Chapter III was conducted to challenge laying hens with reduced dietary P and Ca and describe the effect on GIT active microbiota. The breed was the primary driver of microbial differences. A core microbiome of active bacteria, present along the complete GIT, was revealed for the first time and consisted of five bacteria detected in 97% of all samples, including digesta and mucosa samples (uncl. Lactobacillus, Megamonas funiformis, Ligilactobacillus salivarius, Lactobacillus helveticus, uncl. Fuscatenibacter). Furthermore, significant microbial differences between the GIT sections and between the breeds were described. Minor dietary effects of the P and Ca reduction on the microbiota showed that a further decrease in Ca and P supplementation might be possible without affecting the gut microbial composition and bird performance. Furthermore, the microbiome of laying hens was characterized at five productive stages (weeks 10, 16, 24, 30, and 60) to analyze the age effect on the GIT microbiome (Chapter IV). Although the two breeds of laying hens were offered the same diet and housed under similar conditions, the active microbiota composition changed between the analyzed productive stages, the breed and the GIT sections. The major shift occurred between weeks 16 and 24 and supported the hypothesis of bacterial fluctuations due to the onset of the laying period. Those changes occurred mainly in the abundance of the genera Lactobacillus and Ligilactobacillus. However, it remains unclear whether the dietary changes, due to the development of the birds, influenced the microbiota shifts or if the anatomical and physiological modifications influenced the GIT microbiota. Furthermore, the shotgun metagenomic analysis revealed differences in regulatory functions and pathways between breeds, sections, and the two production stages. Different relative abundance levels of the microbial composition were observed between the RNA-based targeted sequencing and the DNA-based shotgun metagenomics. In conclusion, the comprehensive characterization of the microbiota in the GIT of quails and two high-yielding breeds of laying hens contributes to a broader knowledge of the microbiome dynamics within the fowl GIT. Age and breed play a more important role than diet in influencing the dynamics of microbial composition in laying hens, and individual performance and sex in quails. Research characterizing the microbiome in poultry and its effect on diet and host genetics will help improve feeding and breeding strategies in the future and reduce excretion of nutrients into the environment while ensuring overall animal health.
The effect of aging in the murine gut microbiome
(2020) Hernández Arriaga, Angélica; Camarinha-Silva, Amélia
Aging is characterized by several physiological changes. During the lifespan, the biological systems from the body of humans and other animals remain dynamic. Throughout the early stages of life, the microbiome develops into a complex ecosystem with thousands of species. Variations related to diet, environmental changes, medications affect the diversity and composition of the microbiota through the lifespan. Some old individuals with higher incidence of chronic diseases have a loss of the stability of the microbiome and an imbalance occurs between the different colonizers of the gut, also named dysbiosis. One of the most distinctive changes occurring with age is the prevalent low grade inflammation, which is named inflamm-aging. This not only changes the microbial composition of the GIT but also affects the permeability. Murine models are well established and help us to understand the complex dynamics between the host and the microbial communities inhabiting the gastrointestinal tract. These models allow us to analyze microbial communities from tissue and mucosa, from all sections of the gut, which is limited in humans. Methods standardization is an important topic in microbiome research. In chapter 2 it was compared the efficiency of two sample methods, cotton swab and tissue biopsy, in characterizing the mouth microbiota. In recent years, the mouth microbiome is being seen as a diagnostic tool for not only oral diseases but also systemic diseases. As physiological changes occur with aging, the microbiome from the mouth is affected and there is an increase of pathogens present in the oral surfaces. In murine models, cotton swab is a common tool used for sampling the microbiome of the oral cavity. In our study, we observed similar microbial community structure using both methodologies. However, the species Streptococcus danieliae, Moraxella osloensis, and some unclassified members of Streptococcus were affected by the different sampling procedures. In this trial, we included mice at two different ages, 2 months old being considered young and 15 months old considered middle aged mice. We observed changes in the genera Actinobacillus, Neisseria, Staphylococcus, and Streptococcus related to the age of the animal and the sampling type. These results showed the importance of sampling standardization in microbiome research and that age has a strong effect on the microbial ecology of the oral cavity. In chapter 3, it was studied the bacterial communities from duodenum and colon of mice at 2, 15, 24 and 30 months of age in combination with the results of the expression levels of antimicrobial peptides in small intestine and markers of intestinal barrier function. Besides, in this chapter were also assessed the indices of liver damage, inflammation and expression levels of lipopolysaccharide binding protein (Lbp) as well as of toll-like receptors (Tlr) 1-9 in liver tissues. At 24 and 30 months of age there was an increase in inflammation, they developed fibrosis and the levels of endotoxin in plasma were higher. Regarding changes in the microbiome, the duodenum had more changes than the colon related to age. Allobacullum, Bifidobacterium, Olsenella, Corynebacterium were the genera that differed statistically in the duodenum through the murine lifespan. Fewer changes were observed in the colon, as Allobaculum was the only genus that showed differences between young and old mice. Additionaly, it was analyzed the impact of aging in the active microbial communities of mouth, duodenum and colon at 2, 9, 15, 24 and 30 months of age (chapter 4). Changes were observed at every age and different taxonomical levels, with a greater shift at 15 months of age. This is related to the age of the mice, as at middle age systemic changes related to the aging process start to occur. At old ages, there was an increment of the pathobiontic species Helicobacter hepaticus and Helicobacter ganmani in the duodenum and colon. The oral, duodenal and colonic microbial communities are important pieces of information that can be related to the health status of the host. Research that focuses on assessing the changes in the different niches and not only in the feces, gives a broader overview of the microbial community of the host.
The intestinal microbiome and metabolome of dairy cows under challenging conditions
(2022) Tröscher-Mußotter, Johanna; Seifert, Jana
The modern dairy cow is confronted with a multitude of stressors throughout live. Especially calving, transition, and microbial infections are strong challenges that can have long-lasting impacts on the cow’s health and performance. Yet, individuals can differ in their response towards these challenges, raising the question which characteristics in the dairy cow contribute to a more or less robust animal. Apart from genetics, the gut microbiome and the entailed metabolome is assumed to play an important role in buffering or promoting host stress. This is also due to the fact that the gut microbiome is strongly involved in the hosts energy metabolism and immune system. As dairy cows often show performance impairments during high energy demanding periods, it could be suggested that improving energy metabolism in these specific phases might reduce the negative phenotypic outcomes. This was tested using dietary L-carnitine, a metabolite inevitably necessary for energy metabolism. However, no supplement effects on the intestinal microbiome or metabolome have been found in the present work. Supplementation was continued throughout the complete trial. Calving functioned as an individual stimulus, and an intra-venous LPS injection induced a standardized inflammatory challenge, as a specific amount of LPS per kg of bodyweight was applied per cow. Supplemented animals were compared to a control group. In total, the animals were studied across 168 days and sampled extensively at several sites. The focus of this thesis was to analyze the bacterial consortia and metabolites of both, host and bacteria, in rumen, duodenum, and feces throughout the given period. This was to elucidate the metabolic reactions and bacterial shifts during the mentioned challenging periods and their response to the L-carnitine supplementation. First, the ruminal and duodenal fluid microbiome of eight double cannulated animals during the two respective challenges was analysed. Before calving and feed change, rumen and duodenal fluid bacterial consortia were significantly different, thereafter very alike. Strong microbial community shifts were observed throughout the complete trial irrespectively of the matrix. Both matrices varied in their metabolite patterns indicating functional variation among sites. Also, a strong increase of Bifidobacterium at three days after calving was observed in almost all animals pointing towards a strong biological purpose. This needs to be investigated in upcoming studies. The study could show increasing ketogenic activities in the animals after calving and proposes a possible protective host-microbial interaction, against a ruminal collapse induced by LPS challenge, here described as "microbial airbag". The second part included fecal samples of the same animals, which were analyzed for their bacterial consortia and targeted metabolites. Different dynamics and diversities of microbial communities amongst the individuals were observed, according to which animals could be grouped into three microbiome clusters. These showed in part fundamentally different metabolic, health, and performance parameters, indicating strong host-microbiome-metabolite interactions. The study demonstrated that microbiome clustering may contribute to identifying different metabo- and production types. Again, the study observed a strong increase of Bifidobacterium at three days after calving and even during the LPS challenge supporting the findings of the former study. This strengthens the hypothesis that also for the cow Bifidobacterium may have protective effects, as this genus is largely involved in health promoting activities. The power of this project lies in the massive sampling of different body sites in dairy cows across a very long period of time and finally, merging of the collected data. This, however, requires high computational efforts as numerous time points, matrices, animals, measurements, treatments, feeding regimen, and challenges resulted into a large bandwidth of parameters and metadata. Yet, it bears the potential to better elucidate and understand actions and reactions of the host, its microbiome and metabolism, as well as organ-axes in dairy cows and thereby gaining a more holistic picture of these complex animals. The aim of analyzing the host, its microbiome and metabolome throughout challenging periods resulted into the following main findings. Time, calving, and feed change remarkably change the microbial communities and to a lesser extent the metabolomes in all three matrices. Rumen and proximal duodenal fluid samples significantly differ in their metabolomes but not in their microbiome. In all matrices, an increase of Bifidobacterium is seen within three days after calving, which has to be further researched. Across the herd, three distinct microbiome clusters are found, which significantly differ in their production and health parameters.