scholarly journals Gut microbiota of frugo-folivorous sifakas across environments

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Lydia K. Greene ◽  
Marina B. Blanco ◽  
Elodi Rambeloson ◽  
Karlis Graubics ◽  
Brian Fanelli ◽  
...  

Abstract Background Captive animals, compared to their wild counterparts, generally harbor imbalanced gut microbiota owing, in part, to their altered diets. This imbalance is particularly striking for folivores that fundamentally rely on gut microbiota for digestion, yet rarely receive sufficient dietary fiber in captivity. We examine the critically endangered Coquerel’s sifaka (Propithecus coquereli), an anatomically specialized, rather than facultative, folivore that consumes a seasonal frugo-folivorous diet in the wild, but is provisioned predominantly with seasonal foliage and orchard vegetables in captivity. Using amplicon and metagenomic sequencing applied to fecal samples collected from two wild and one captive population (each comprising multiple groups), we clarify how dietary variation underlies the perturbational effect of captivity on the structure and function of this species’ gut microbiota. Results The gut microbiota of wild sifakas varied by study population, most notably in community evenness and in the abundance of diet-associated microbes from Prevotellaeceae and Lachnospiraceae. Nevertheless, the differences among wild subjects were minor compared to those evident between wild and captive sifakas: Unusually, the consortia of captive sifakas were the most diverse, but lacked representation of endemic Bacteroidetes and metagenomic capacity for essential amino-acid biosynthesis. Instead, they were enriched for complex fiber metabolizers from the Firmicutes phylum, for archaeal methanogens, and for several metabolic pathways putatively linked to plant fiber and secondary compound metabolism. Conclusions The relatively minor differences in gut microbial structure and function between wild sifaka populations likely reflect regional and/or temporal environmental variability, whereas the major differences observed in captive conspecifics, including the loss of endemic microbes, but gain in low-abundance taxa, likely reflect imbalanced or unstable consortia. Indeed, community perturbation may not necessarily entail decreased community diversity. Moreover, signatures of greater fiber degradation indicate that captive sifakas consume a more fibrous diet compared to their wild counterparts. These results do not mirror those typically reported for folivores and herbivores, suggesting that the direction and strength of captivity-induced ‘dysbiosis’ may not be universal across species with similar feeding strategies. We propose that tailored, species-specific dietary interventions in captivity, aimed at better approximating naturally foraged diets, could functionally ‘rewild’ gut microbiota and facilitate successful management of diverse species.

2020 ◽  
Vol 71 (1) ◽  
pp. 149-161 ◽  
Author(s):  
Ilias Attaye ◽  
Sara-Joan Pinto-Sietsma ◽  
Hilde Herrema ◽  
Max Nieuwdorp

Cardiometabolic disease (CMD), such as type 2 diabetes mellitus and cardiovascular disease, contributes significantly to morbidity and mortality on a global scale. The gut microbiota has emerged as a potential target to beneficially modulate CMD risk, possibly via dietary interventions. Dietary interventions have been shown to considerably alter gut microbiota composition and function. Moreover, several diet-derived microbial metabolites are able to modulate human metabolism and thereby alter CMD risk. Dietary interventions that affect gut microbiota composition and function are therefore a promising, novel, and cost-efficient method to reduce CMD risk. Studies suggest that fermentable carbohydrates can beneficially alter gut microbiota composition and function, whereas high animal protein and high fat intake negatively impact gut microbiota function and composition. This review focuses on the role of macronutrients (i.e., carbohydrate, protein, and fat) and dietary patterns (e.g., vegetarian/vegan and Mediterranean diet) in gut microbiota composition and function in the context of CMD.


mSystems ◽  
2016 ◽  
Vol 1 (5) ◽  
Author(s):  
Samuel A. Smits ◽  
Angela Marcobal ◽  
Steven Higginbottom ◽  
Justin L. Sonnenburg ◽  
Purna C. Kashyap

ABSTRACT Dietary modification has long been used empirically to modify symptoms in inflammatory bowel disease, irritable bowel syndrome, and a diverse group of diseases with gastrointestinal symptoms. There is both anecdotal and scientific evidence to suggest that individuals respond quite differently to similar dietary changes, and the highly individualized nature of the gut microbiota makes it a prime candidate for these differences. To overcome the typical confounding factors of human dietary interventions, here we employ ex-germfree mice colonized by microbiotas of three different humans to test how different microbiotas respond to a defined change in carbohydrate content of diet by measuring changes in microbiota composition and function using marker gene-based next-generation sequencing and metabolomics. Our findings suggest that the same diet has very different effects on each microbiota’s membership and function, which may in turn explain interindividual differences in response to a dietary ingredient. Diet plays an important role in shaping the structure and function of the gut microbiota. The microbes and microbial products in turn can influence various aspects of host physiology. One promising route to affect host function and restore health is by altering the gut microbiome using dietary intervention. The individuality of the microbiome may pose a significant challenge, so we sought to determine how different microbiotas respond to the same dietary intervention in a controlled setting. We modeled gut microbiotas from three healthy donors in germfree mice and defined compositional and functional alteration following a change in dietary microbiota-accessible carbohydrates (MACs). The three gut communities exhibited responses that differed markedly in magnitude and in the composition of microbiota-derived metabolites. Adjustments in community membership did not correspond to the magnitude of changes in the microbial metabolites, highlighting potential challenges in predicting functional responses from compositional data and the need to assess multiple microbiota parameters following dietary interventions. IMPORTANCE Dietary modification has long been used empirically to modify symptoms in inflammatory bowel disease, irritable bowel syndrome, and a diverse group of diseases with gastrointestinal symptoms. There is both anecdotal and scientific evidence to suggest that individuals respond quite differently to similar dietary changes, and the highly individualized nature of the gut microbiota makes it a prime candidate for these differences. To overcome the typical confounding factors of human dietary interventions, here we employ ex-germfree mice colonized by microbiotas of three different humans to test how different microbiotas respond to a defined change in carbohydrate content of diet by measuring changes in microbiota composition and function using marker gene-based next-generation sequencing and metabolomics. Our findings suggest that the same diet has very different effects on each microbiota’s membership and function, which may in turn explain interindividual differences in response to a dietary ingredient. Author Video: An author video summary of this article is available.


mSystems ◽  
2018 ◽  
Vol 3 (6) ◽  
Author(s):  
Jingwei Cai ◽  
Robert G. Nichols ◽  
Imhoi Koo ◽  
Zachary A. Kalikow ◽  
Limin Zhang ◽  
...  

ABSTRACTThe gut microbiota is susceptible to modulation by environmental stimuli and therefore can serve as a biological sensor. Recent evidence suggests that xenobiotics can disrupt the interaction between the microbiota and host. Here, we describe an approach that combinesin vitromicrobial incubation (isolated cecal contents from mice), flow cytometry, and mass spectrometry- and1H nuclear magnetic resonance (NMR)-based metabolomics to evaluate xenobiotic-induced microbial toxicity. Tempol, a stabilized free radical scavenger known to remodel the microbial community structure and functionin vivo, was studied to assess its direct effect on the gut microbiota. The microbiota was isolated from mouse cecum and was exposed to tempol for 4 h under strict anaerobic conditions. The flow cytometry data suggested that short-term tempol exposure to the microbiota is associated with disrupted membrane physiology as well as compromised metabolic activity. Mass spectrometry and NMR metabolomics revealed that tempol exposure significantly disrupted microbial metabolic activity, specifically indicated by changes in short-chain fatty acids, branched-chain amino acids, amino acids, nucleotides, glucose, and oligosaccharides. In addition, a mouse study with tempol (5 days gavage) showed similar microbial physiologic and metabolic changes, indicating that thein vitroapproach reflectedin vivoconditions. Our results, through evaluation of microbial viability, physiology, and metabolism and a comparison ofin vitroandin vivoexposures with tempol, suggest that physiologic and metabolic phenotyping can provide unique insight into gut microbiota toxicity.IMPORTANCEThe gut microbiota is modulated physiologically, compositionally, and metabolically by xenobiotics, potentially causing metabolic consequences to the host. We recently reported that tempol, a stabilized free radical nitroxide, can exert beneficial effects on the host through modulation of the microbiome community structure and function. Here, we investigated a multiplatform phenotyping approach that combines high-throughput global metabolomics with flow cytometry to evaluate the direct effect of tempol on the microbiota. This approach may be useful in deciphering how other xenobiotics directly influence the microbiota.


PLoS ONE ◽  
2013 ◽  
Vol 8 (11) ◽  
pp. e80201 ◽  
Author(s):  
Ana Elena Pérez-Cobas ◽  
Alejandro Artacho ◽  
Henrik Knecht ◽  
María Loreto Ferrús ◽  
Anette Friedrichs ◽  
...  

2021 ◽  
Author(s):  
Noel T. Mueller ◽  
Moira K. Differding ◽  
Mingyu Zhang ◽  
Nisa Maruthar ◽  
Stephen P Juraschek ◽  
...  

<b>Objective:</b> To determine the longer-term effects of metformin and behavioral weight loss on gut microbiota and SCFAs. <p><b>Methods: </b>We conducted a parallel-arm, randomized trial. We enrolled overweight/obese adults who had been treated for solid tumors but had no ongoing cancer treatment and randomized them (n=121) to: 1) metformin (up to 2000mg), 2) coach-directed behavioral weight loss, or 3) self-directed care (control) for 12 months. We collected stool and serum at baseline (n=114), 6 months (n=109) and 12 months (n=105). From stool, we extracted microbial DNA and conducted amplicon and metagenomic sequencing. We measured SCFAs and other biochemical parameters from fasting serum. </p> <p><b>Results: </b>Of the 121 participants, 79% were female, 46% were black, and the mean age was 60y. Only metformin intervention significantly altered microbiota composition. Compared to control, metformin increased <i>E. Coli</i> and <i>Ruminococcus torques</i> and decreased <i>Intestinibacter Bartletti</i> at both 6 and 12 months, and decreased the genus <i>Roseburia (genus)</i>, including <i>R. faecis</i> and <i>R. intestinalis,</i> at 12 months. Effects were similar when comparing metformin to the behavioral weight loss group. Metformin also altered 62 metagenomic functional pathways and increased butyrate, acetate, and valerate at 6 months. Behavioral weight loss vs. control did not significantly alter microbiota composition, but did increase acetate at 6 months. Increases in acetate were associated with decreases in fasting insulin.</p> <p><b>Conclusions:</b> Metformin, but not behavioral weight loss, impacted gut microbiota composition and function at 6 months and 12 months. Both metformin and behavioral weight loss altered 6-month SCFAs, including increasing acetate which correlated with improved insulin sensitivity.</p>


2021 ◽  
Vol 12 ◽  
Author(s):  
Runbiao Wu ◽  
Luyu Wang ◽  
Jianping Xie ◽  
Zhisheng Zhang

Wolf spiders (Lycosidae) are crucial component of integrated pest management programs and the characteristics of their gut microbiota are known to play important roles in improving fitness and survival of the host. However, there are only few studies of the gut microbiota among closely related species of wolf spider. Whether wolf spiders gut microbiota vary with habitats remains unknown. Here, we used shotgun metagenomic sequencing to compare the gut microbiota of two wolf spider species, Pardosa agraria and P. laura from farmland and woodland ecosystems, respectively. The results show that the gut microbiota of Pardosa spiders is similar in richness and abundance. Approximately 27.3% of the gut microbiota of P. agraria comprises Proteobacteria, and approximately 34.5% of the gut microbiota of P. laura comprises Firmicutes. We assembled microbial genomes and found that the gut microbiota of P. laura are enriched in genes for carbohydrate metabolism. In contrast, those of P. agraria showed a higher proportion of genes encoding acetyltransferase, an enzyme involved in resistance to antibiotics. We reconstructed three high-quality and species-level microbial genomes: Vulcaniibacterium thermophilum, Anoxybacillus flavithermus and an unknown bacterium belonging to the family Simkaniaceae. Our results contribute to an understanding of the diversity and function of gut microbiota in closely related spiders.


Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Fernando A. Vicentini ◽  
Catherine M. Keenan ◽  
Laurie E. Wallace ◽  
Crystal Woods ◽  
Jean-Baptiste Cavin ◽  
...  

Abstract Background The intestinal microbiota plays an important role in regulating gastrointestinal (GI) physiology in part through interactions with the enteric nervous system (ENS). Alterations in the gut microbiome frequently occur together with disturbances in enteric neural control in pathophysiological conditions. However, the mechanisms by which the microbiota regulates GI function and the structure of the ENS are incompletely understood. Using a mouse model of antibiotic (Abx)-induced bacterial depletion, we sought to determine the molecular mechanisms of microbial regulation of intestinal function and the integrity of the ENS. Spontaneous reconstitution of the Abx-depleted microbiota was used to assess the plasticity of structure and function of the GI tract and ENS. Microbiota-dependent molecular mechanisms of ENS neuronal survival and neurogenesis were also assessed. Results Adult male and female Abx-treated mice exhibited alterations in GI structure and function, including a longer small intestine, slower transit time, increased carbachol-stimulated ion secretion, and increased intestinal permeability. These alterations were accompanied by the loss of enteric neurons in the ileum and proximal colon in both submucosal and myenteric plexuses. A reduction in the number of enteric glia was only observed in the ileal myenteric plexus. Recovery of the microbiota restored intestinal function and stimulated enteric neurogenesis leading to increases in the number of enteric glia and neurons. Lipopolysaccharide (LPS) supplementation enhanced neuronal survival alongside bacterial depletion, but had no effect on neuronal recovery once the Abx-induced neuronal loss was established. In contrast, short-chain fatty acids (SCFA) were able to restore neuronal numbers after Abx-induced neuronal loss, demonstrating that SCFA stimulate enteric neurogenesis in vivo. Conclusions Our results demonstrate a role for the gut microbiota in regulating the structure and function of the GI tract in a sex-independent manner. Moreover, the microbiota is essential for the maintenance of ENS integrity, by regulating enteric neuronal survival and promoting neurogenesis. Molecular determinants of the microbiota, LPS and SCFA, regulate enteric neuronal survival, while SCFA also stimulates neurogenesis. Our data reveal new insights into the role of the gut microbiota that could lead to therapeutic developments for the treatment of enteric neuropathies.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 18-18
Author(s):  
Feng-Qi Liu ◽  
Qi Chen ◽  
Qingyuan Qu ◽  
Xueyan Sun ◽  
Qiu-Sha Huang ◽  
...  

Abstract Introduction Growing evidence has implicated gut microbiota in the pathogenesis of immune thrombocytopenia (ITP). In a previous research study, we found dysbiosis in the phylogenetic composition and function of gut microbiome in ITP and that corticosteroid treatment may have a strong effect on gut microbiota [Sci China Life Sci, 2020]. Corticosteroids have been widely used in the initial treatment of newly diagnosed ITP patients, but most adult patients relapse upon cessation of steroid treatment. Patients on agents in subsequent therapy may improve at any time, but which patients improve and when is unpredictable. The gut microbiome has been increasingly used in the assessment and prediction of immunomodulatory therapy in autoimmune diseases and cellular immunotherapy in cancers. Here, we provide evidence that gut microbiota and function signatures can be used to predict immune thrombocytopenia patients at high risk of relapse/resistance after corticosteroid treatment and to identify patients that are more likely to benefit from TPO-RAs in subsequent therapy. Methods Seventy-five fecal samples from 60 patients with newly diagnosed ITP (60 specimens before corticosteroid therapy and 15 specimens after corticosteroid therapy) and 41 samples from persistent/chronic ITP before and after treatment with TPO-RAs, including eltrombopag and avatrombopag were collected for deep shotgun metagenomic sequencing. To identify the microbial biomarkers related to relapse/resistance after corticosteroid treatment, we constructed a random forest classifier using machine learning to determine the risk of relapse/resistance of a training cohort of 30 patients from baseline samples and validated the classifier for 30 patients. Patients with persistent/chronic ITP were divided into responders and nonresponders according to their response to TPO-RA treatment in subsequent therapy. After identifying the microbial species and functional biomarkers related to the response to TPO-RA therapy, a random forest classifier was constructed using a training set of 20 patients and validated using a validation set of 21 patients. Results We used a metagenomic sequencing technique to investigate the differences among gut microbiota associated with relapse within 3 months of corticosteroid treatment. We observed that the diversity and composition of the microbial community in ITP patients after corticosteroid therapy (Post-C) changed significantly from the baseline (Pre-C), whereas the gut microbiota of the remission group was similar to that of the HC group, which implies that a shift in the gut microbiome could represent a return to homeostasis. To identify the microbial biomarkers related to early relapse after corticosteroid treatment, the Pre-C samples were divided into a remission group and a resistant/relapse group according to the response to corticosteroid therapy within 3 months. Nine significant associations with the microbial species and function were identified between the remission and resistant/relapse groups. A risk index built from this panel of microbes and functional pathways was used to differentiate remission from resistant/relapsed patients based on the baseline characteristics. The receiver operating characteristic (ROC) curve demonstrated that the risk index was a strong predictor of treatment response, with an area under the curve (AUC) of 0.87. Furthermore, to predict the response to TPO-RAs in subsequent therapy, the baseline gut microbiomes of responders and nonresponders before TPO-RA treatment were compared. Patients who responded to treatment exhibited an increase in Ruminococcaceae, Clostridiaceae and Bacteroides compared to nonresponders, with elevated abundance of the phosphotransferase system, tyrosine metabolism and secondary bile acid biosynthesis pathways according to KEGG analysis. Our prediction model based on the gut microbiome for TPO-RA response was robust across the cohorts and showed 89.5% and 79.2% prediction accuracy for persistent/chronic ITP patients in the training and validation sets, respectively. Conclusions The gut microbiome and function signatures based on machine learning analysis are novel potential biomarkers for predicting resistance/relapse after corticosteroid treatment and response to TPO-RAs, which may have important manifestations in the clinical. Disclosures No relevant conflicts of interest to declare.


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