The intestinal microbiota influence neurodevelopment, modulate behavior, and contribute to neurological disorders. However, a functional link between gut bacteria and neurodegenerative diseases ...remains unexplored. Synucleinopathies are characterized by aggregation of the protein α-synuclein (αSyn), often resulting in motor dysfunction as exemplified by Parkinson’s disease (PD). Using mice that overexpress αSyn, we report herein that gut microbiota are required for motor deficits, microglia activation, and αSyn pathology. Antibiotic treatment ameliorates, while microbial re-colonization promotes, pathophysiology in adult animals, suggesting that postnatal signaling between the gut and the brain modulates disease. Indeed, oral administration of specific microbial metabolites to germ-free mice promotes neuroinflammation and motor symptoms. Remarkably, colonization of αSyn-overexpressing mice with microbiota from PD-affected patients enhances physical impairments compared to microbiota transplants from healthy human donors. These findings reveal that gut bacteria regulate movement disorders in mice and suggest that alterations in the human microbiome represent a risk factor for PD.
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•Gut microbes promote α-synuclein-mediated motor deficits and brain pathology•Depletion of gut bacteria reduces microglia activation•SCFAs modulate microglia and enhance PD pathophysiology•Human gut microbiota from PD patients induce enhanced motor dysfunction in mice
Signals from gut microbes are required for the neuroinflammatory responses as well as hallmark gastrointestinal and α-synuclein-dependent motor deficits in a model of Parkinson’s disease.
The gut microbiome is emerging as a key modulator of human energy balance. Prior studies in humans lacked the environmental and dietary controls and precision required to quantitatively evaluate the ...contributions of the gut microbiome. Using a Microbiome Enhancer Diet (MBD) designed to deliver more dietary substrates to the colon and therefore modulate the gut microbiome, we quantified microbial and host contributions to human energy balance in a controlled feeding study with a randomized crossover design in young, healthy, weight stable males and females (NCT02939703). In a metabolic ward where the environment was strictly controlled, we measured energy intake, energy expenditure, and energy output (fecal and urinary). The primary endpoint was the within-participant difference in host metabolizable energy between experimental conditions Control, Western Diet (WD) vs. MBD. The secondary endpoints were enteroendocrine hormones, hunger/satiety, and food intake. Here we show that, compared to the WD, the MBD leads to an additional 116 ± 56 kcals (P < 0.0001) lost in feces daily and thus, lower metabolizable energy for the host (89.5 ± 0.73%; range 84.2-96.1% on the MBD vs. 95.4 ± 0.21%; range 94.1-97.0% on the WD; P < 0.0001) without changes in energy expenditure, hunger/satiety or food intake (P > 0.05). Microbial 16S rRNA gene copy number (a surrogate of biomass) increases (P < 0.0001), beta-diversity changes (whole genome shotgun sequencing; P = 0.02), and fermentation products increase (P < 0.01) on an MBD as compared to a WD along with significant changes in the host enteroendocrine system (P < 0.0001). The substantial interindividual variability in metabolizable energy on the MBD is explained in part by fecal SCFAs and biomass. Our results reveal the complex host-diet-microbiome interplay that modulates energy balance.
Butyrate is a common fatty acid produced in important fermentative systems, such as the human/animal gut and other H 2 production systems. Despite its importance, there is little information on the ...partnerships between butyrate producers and other bacteria. The objective of this work was to uncover butyrateproducing microbial communities and possible metabolic routes in a controlled fermentation system aimed at butyrate production. The butyrogenic reactor was operated at 37°C and pH 5.5 with a hydraulic retention time of 31 h and a low hydrogen partial pressure (PH 2). High-throughput sequencing and metagenome functional prediction from 16S rRNA data showed that butyrate production pathways and microbial communities were different during batch (closed) and continuousmode operation. Lactobacillaceae, Lachnospiraceae, and Enterococcaceae were the most abundant phylotypes in the closed system without PH 2 control, whereas Prevotellaceae, Ruminococcaceae, and Actinomycetaceae were the most abundant phylotypes under continuous operation at low PH 2. Putative butyrate producers identified in our system were from Prevotellaceae, Clostridiaceae, Ruminococcaceae, and Lactobacillaceae. Metagenome prediction analysis suggests that nonbutyrogenic microorganisms influenced butyrate production by generating butyrate precursors such as acetate, lactate, and succinate. 16S rRNA gene analysis suggested that, in the reactor, a partnership between identified butyrogenic microorganisms and succinate (i.e., Actinomycetaceae), acetate (i.e., Ruminococcaceae and Actinomycetaceae), and lactate producers (i.e., Ruminococcaceae and Lactobacillaceae) took place under continuousflow operation at low PH 2. IMPORTANCE This study demonstrates how bioinformatics tools, such as metagenome functional prediction from 16S rRNA genes, can help understand biological systems and reveal microbial interactions in controlled systems (e.g., bioreactors). Results obtained from controlled systems are easier to interpret than those from human/animal studies because observed changes may be specifically attributed to the design conditions imposed on the system. Bioinformatics analysis allowed us to identify potential butyrogenic phylotypes and associated butyrate metabolism pathways when we systematically varied the PH 2 in a carefully controlled fermentation system. Our insights may be adapted to butyrate production studies in biohydrogen systems and gut models, since butyrate is a main product and a crucial fatty acid in human/animal colon health. KEYWORDS butyrate production pathways, PICRUSt, Prevotellaceae, hydrogen partial pressure, interconversion reactions, predicted metagenome functional content F ermentation involves the degradation of organic material by anaerobic microorganisms in an environment with low dissolved oxygen and produces short-chain fatty acids (SCFA) (e.g., butyrate and acetate) and gases, including methane (CH 4),
Background The large intestine provides a compensatory role in energy recovery when surgical interventions such as extensive small intestinal resections or bypass operations lower the efficiency of ...nutrient absorption in the upper gastrointestinal (GI) tract. While microorganisms in the colon are known to play vital roles in recovering energy, their contributions remain to be qualified and quantified in the small intestine resection. Objective We develop a mathematical model that links nutrient absorption in the upper and lower GI tract in two steps. Methods First, we describe the effects of small intestine resection on the ileocecal output (ICO), which enters the colon and provides food for microbes. Second, we describe energy recovered by the colon's microorganisms via short-chain fatty acid (SCFA) production. We obtain model parameters by performing a least-squares regression analysis on clinical data for subjects with normal physiology and those who had undergone small intestine resection. Results For subjects with their intestines intact, our model provided a metabolizable energy value that aligns well with the traditional Atwater coefficients. With removal of the small intestine, physiological absorption became less efficient, and the metabolizable energy decreased. In parallel, the inefficiencies in physiological absorption by the small intestine are partly compensated by production of short-chain fatty acids (SCFA) from proteins and carbohydrates by microorganisms in the colon. The colon recovered more than half of the gross energy intake when the entire small intestine was removed. Meanwhile, the quality of energy absorbed changed, because microbe-derived SCFAs, not the original components of food, become the dominant form of absorbed energy. Conclusion The mathematical model developed here provides an important framework for describing the effect of clinical interventions on the colon's microorganisms.
Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and ...molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education.
We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating
= 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.
There is a growing body of scientific evidence that the health of the microbiome (the trillions of microbes that inhabit the human host) plays an important role in maintaining the health of the host ...and that disruptions in the microbiome may play a role in certain disease processes. An increasing number of research studies have provided evidence that the composition of the gut (enteric) microbiome (GM) in at least a subset of individuals with autism spectrum disorder (ASD) deviates from what is usually observed in typically developing individuals. There are several lines of research that suggest that specific changes in the GM could be causative or highly associated with driving core and associated ASD symptoms, pathology, and comorbidities which include gastrointestinal symptoms, although it is also a possibility that these changes, in whole or in part, could be a consequence of underlying pathophysiological features associated with ASD. However, if the GM truly plays a causative role in ASD, then the manipulation of the GM could potentially be leveraged as a therapeutic approach to improve ASD symptoms and/or comorbidities, including gastrointestinal symptoms. One approach to investigating this possibility in greater detail includes a highly controlled clinical trial in which the GM is systematically manipulated to determine its significance in individuals with ASD. To outline the important issues that would be required to design such a study, a group of clinicians, research scientists, and parents of children with ASD participated in an interdisciplinary daylong workshop as an extension of the 1st International Symposium on the Microbiome in Health and Disease with a Special Focus on Autism (
www.microbiome-autism.com
). The group considered several aspects of designing clinical studies, including clinical trial design, treatments that could potentially be used in a clinical trial, appropriate ASD participants for the clinical trial, behavioral and cognitive assessments, important biomarkers, safety concerns, and ethical considerations. Overall, the group not only felt that this was a promising area of research for the ASD population and a promising avenue for potential treatment but also felt that further basic and translational research was needed to clarify the clinical utility of such treatments and to elucidate possible mechanisms responsible for a clinical response, so that new treatments and approaches may be discovered and/or fostered in the future.
Human and microbial metabolism are distinct disciplines. Terminology, metrics, and methodologies have been developed separately. Therefore, combining the 2 fields to study energetic processes ...simultaneously is difficult.
When developing a mechanistic framework describing gut microbiome and human metabolism interactions, energy values of food and digestive materials that use consistent and compatible metrics are required. As an initial step toward this goal, we developed and validated a model to convert between chemical oxygen demand (COD) and gross energy (Eg) for >100 food items and ingredients.
We developed linear regression models to relate (and be able to convert between) theoretical gross energy (Eg') and chemical oxygen demand (COD′); the latter is a measure of electron equivalents in the food's carbon. We developed an overall regression model for the food items as a whole and separate regression models for the carbohydrate, protein, and fat components. The models were validated using a sample set of computed Eg' and COD′ values, an experimental sample set using measured Eg and COD values, and robust statistical methods.
The overall linear regression model and the carbohydrate, protein, and fat regression models accurately converted between COD and Eg, and the component models had smaller error. Because the ratios of COD per gram dry weight were greatest for fats and smallest for carbohydrates, foods with a high fat content also had higher Eg values in terms of kcal · g dry weight−1.
Our models make it possible to analyze human and microbial energetic processes in concert using a single unit of measure, which fills an important need in the food–nutrition–metabolism–microbiome field. In addition, measuring COD and using the regressions to calculate Eg can be used instead of measuring Eg directly using bomb calorimetry, which saves time and money.
Immunopathogenesis in systemic viral infections can induce a septic state with leaky capillary syndrome, disseminated coagulopathy, and high mortality with limited treatment options. Murine ...gammaherpesvirus-68 (MHV-68) intraperitoneal infection is a gammaherpesvirus model for producing severe vasculitis, colitis and lethal hemorrhagic pneumonia in interferon gamma receptor-deficient (IFNγR
) mice. In prior work, treatment with myxomavirus-derived Serp-1 or a derivative peptide S-7 (G
TTASSDTAITLIPR
) induced immune protection, reduced disease severity and improved survival after MHV-68 infection. Here, we investigate the gut bacterial microbiome in MHV-68 infection. Antibiotic suppression markedly accelerated MHV-68 pathology causing pulmonary consolidation and hemorrhage, increased mortality and specific modification of gut microbiota. Serp-1 and S-7 reduced pulmonary pathology and detectable MHV-68 with increased CD3 and CD8 cells. Treatment efficacy was lost after antibiotic treatments with associated specific changes in the gut bacterial microbiota. In summary, transkingdom host-virus-microbiome interactions in gammaherpesvirus infection influences gammaherpesviral infection severity and reduces immune modulating therapeutic efficacy.
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