Project description:Microbiota-released extracellular vesicles (MEVs) have emerged as a key player in intercellular signaling. However, their involvement in the gut-brain axis has been poorly investigated. In this study, we aimed to investigate the cargo capacity of MEVs for bioactive metabolites and their interactions with the host. Metabolomics analysis identified various neuro-related compounds encapsulated within the 28 MEVs, such as arachidonyl-dopamine, gabapentin, glutamate, and N-acylethanolamines. 29 Metaproteomics unveiled an enrichment of enzymes involved in neuronal metabolism, primarily in the glutamine/glutamate/GABA pathway. The detected neuro-related proteins and metabolites were correlated with Bacteroides spp. A GABA-producing Bacteroides isolate, B. finegoldii, released EVs with a high GABA content (4 µM) as opposed to a low GABA-producing isolate, Phocaeicola massiliensis. MEVs exhibited a dose-dependent paracellular transport and were endocytosed by Caco-2 and hCMEC/D3 cells. RNA-Seq analyses showed that MEVs stimulate several immune pathways while suppressing cell apoptosis process. The in vivo biodistribution confirmed the presence of MEVs in the brain, liver, stomach, and spleen. Overall, our results highlight the ability of MEVs to cross the intestinal and blood-brain barriers to deliver their cargoes to distant organs, including the brain, where it may modulate the organ functionalities. MEVs could be an integral part of microbiome-host communications, with potential implication for the gut-brain axis.
Project description:Introduction. A substantial number of Crohn’s disease (CD) patients experience side-effects and/or non-response to medical drugs. In part, this might be attributed to the interaction of the intestinal microbiome with xenobiotics. The aim of this study was to explore the effect of common CD drugs on the patient’s microbiome in vitro. Methods The fecal microbiome of each of 5 CD patients was exposed to 42 μg/ml budesonide, 55 μg/ml 6-mercaptopurine (6-MP), 5 or 15 μg/ml tofacitinib, or DMSO-control in defined culture medium in an anaerobic chamber at 37°C for 24 hours. Subsequently, DNA and proteins were isolated and subjected to 16 rRNA gene amplicon sequencing and LC-MS proteomic analysis, respectively.
Project description:The gut microbiome's pivotal role in health and disease is well-established. SARS-CoV-2 infection often causes gastrointestinal symptoms and is associated with changes of the microbiome in both human and animal studies. While hamsters serve as important animal models for coronavirus research, there exists a notable void in the functional characterization of their microbiomes with metaproteomics. In this study, we present a workflow for analyzing the hamster gut microbiome, including a metagenomics-derived hamster gut microbial protein database and a data-independent acquisition metaproteomics method. Using this workflow, we identified 32419 protein groups from the fecal microbiomes of young and old hamsters infected with SARS-CoV-2. We showed age-specific changes in the expressions of microbiome functions and host proteins associated with microbiomes, providing further functional insight into the dysbiosis and aberrant cross-talks between the microbiome and host in SARS-CoV-2 infection. Altogether this study established and demonstrated the capability of metaproteomics for the study of hamster microbiomes.
Project description:Seasonal influenza outbreaks represent a large burden for the healthcare system as well as the economy. While the role of the microbiome in the context of various diseases has been elucidated, the effects on the respiratory and gastrointestinal microbiome during influenza illness is largely unknown. Therefore, this study aimed to characterize the temporal development of the respiratory and gastrointestinal microbiome of swine using a multi-omics approach prior and during influenza infection. Swine is a suitable animal model for influenza research, as it is closely related to humans and a natural host for influenza viruses. Our results showed that IAV infection resulted in significant changes in the abundance of Moraxellaceae and Pasteurellaceae families in the upper respiratory tract. To our surprise, temporal development of the respiratory microbiome was not affected. Furthermore, we observed significantly altered microbial richness and diversity in the gastrointestinal microbiome after IAV infection. In particular, we found increased abundances of Prevotellaceae, while Clostridiaceae and Lachnospiraceae decreased. Furthermore, metaproteomics showed that the functional composition of the microbiome, known to be robust and stable under healthy conditions, was heavily affected by the influenza infection. Metabolome analysis proved increased amounts of short-chain fatty acids in the gastrointestinal tract, which might be involved in faster recovery. Furthermore, metaproteome data suggest a possible immune response towards flagellated Clostridia induced during the infection. Therefore, it can be assumed that the respiratory infection with IAV caused a systemic effect in the porcine host and microbiome.
Project description:We developed an approach named Rapid Assay of Individual Microbiome (RapidAIM) to screen xenobiotics against individual microbiomes. To evaluate technical reproducibility, we tested 43 compounds against an individual's microbiome. The individual microbiome is cultured in triplicates in 96-well plates for 24 hours and the samples are then analyzed using a metaproteomics-based analytical approach to gain functional insight into the individual microbiomes responses following drug treatments.The tested compounds significantly affected overall microbiome abundance, microbiome composition and functional pathways at multiple taxonomic levels. The microbiome responses to berberine, metformin, diclofenac, fructooligosaccharide and most antibiotics were consistent among most individual microbiomes. Interestingly, most of our tested NSAIDs, statins, and histamine-2 blockers induced individually distinct responses. Our workflow offers an effective solution to systematically study the effects of many different compounds on individual microbiomes.
Project description:We developed an approach named Rapid Assay of Individual Microbiome (RapidAIM) to screen xenobiotics against individual microbiomes, and conducted a proof-of-concept (POC) study on the use of RapidAIM. We tested 43 compounds against five individual microbiomes. The individual microbiomes are cultured in 96-well plates for 24 hours and the samples are then analyzed using a metaproteomics-based analytical approach to gain functional insight into the individual microbiomes responses following drug treatments.The tested compounds significantly affected overall microbiome abundance, microbiome composition and functional pathways at multiple taxonomic levels. The microbiome responses to berberine, metformin, diclofenac, fructooligosaccharide and most antibiotics were consistent among most individual microbiomes. Interestingly, most of our tested NSAIDs, statins, and histamine-2 blockers induced individually distinct responses. Our workflow offers an effective solution to systematically study the effects of many different compounds on individual microbiomes.
Project description:Here, we quantify the proteome-level functional redundancy in the human gut microbiome using metaproteomics and network approaches.In particular, we used an ultra-deep metaproteomics approach based on high-pH reverse phase fractionation. The data analysis revealed high protein-level functional redundancy and high nestedness in proteomic content networks - bipartite graphs that connect taxa with their expressed functions.
Project description:Aging is associated with declining immunity and inflammation as well as alterations in the gut microbiome with a decrease of beneficial microbes and increase in pathogenic ones. The aim of this study was to investigate aging associated gut microbiome in relation to immunologic and metabolic profile in a non-human primate (NHP) model. 12 old (age>18 years) and 4 young (age 3-6 years) Rhesus macaques were included in this study. Immune cell subsets were characterized in PBMC by flow cytometry and plasma cytokines levels were determined by bead based multiplex cytokine analysis. Stool samples were collected by ileal loop and investigated for microbiome analysis by shotgun metagenomics. Serum, gut microbial lysate and microbe-free fecal extract were subjected to metabolomic analysis by mass-spectrometry. Our results showed that the old animals exhibited higher inflammatory biomarkers in plasma and lower CD4 T cells with altered distribution of naïve and memory T cell maturation subsets. The gut microbiome in old animals had higher abundance of Archaeal and Proteobacterial species and lower Firmicutes than the young. Significant enrichment of metabolites that contribute to inflammatory and cytotoxic pathways was observed in serum and feces of old animals compared to the young. We conclude that aging NHP undergo immunosenescence and age associated alterations in the gut microbiome that has a distinct metabolic profile.
Project description:Pancreatic cancer is the 3rd most prevalent cause of cancer related deaths in United states alone, with over 55000 patients being diagnosed in 2019 alone and nearly as many succumbing to it. Late detection, lack of effective therapy and poor understanding of pancreatic cancer systemically contributes to its poor survival statistics. Obesity and high caloric intake linked co-morbidities like type 2 diabetes (T2D) have been attributed as being risk factors for a number of cancers including pancreatic cancer. Studies on gut microbiome has shown that lifestyle factors as well as diet has a huge effect on the microbial flora of the gut. Further, modulation of gut microbiome has been seen to contribute to effects of intensive insulin therapy in mice on high fat diet. In another study, abnormal gut microbiota was reported to contribute to development of diabetes in Db/Db mice. Recent studies indicate that microbiome and microbial dysbiosis plays a role in not only the onset of disease but also in its outcome. In colorectal cancer, Fusobacterium has been reported to promote therapy resistance. Certain intra-tumoral bacteria have also been shown to elicit chemo-resistance by metabolizing anti-cancerous agents. In pancreatic cancer, studies on altered gut microbiome have been relatively recent. Microbial dysbiosis has been observed to be associated with pancreatic tumor progression. Modulation of microbiome has been shown to affect response to anti-PD1 therapy in this disease as well. However, most of the studies in pancreatic cancer and microbiome have remained focused om immune modulation. In the current study, we observed that in a T2D mouse model, the microbiome changed significantly as the hyperglycemia developed in these animals. Our results further showed that, tumors implanted in the T2D mice responded poorly to Gemcitabine/Paclitaxel (Gem/Pac) standard of care compared to those in the control group. A metabolomic reconstruction of the WGS of the gut microbiota further revealed that an enrichment of bacterial population involved in drug metabolism in the T2D group.
Project description:We developed a free-flow isoelectric focusing (FFIEF) based metaproteomics workflow to reduce the host interferences and enrich the low-abundant bacteria for better interpretation of salivary microbiome. We firstly tested the pretreatment module that could significantly reduce the host interferences by differential centrifugation and filtration. Then the FFIEF module was applied to separate the microbes and enrich the low-abundant bacteria, which showed a significant improvement in the identification efficiency of microbiome sample. Applying our method to lung cancer, we successfully identified Fusobacterium, Neisseriaceae, Actinomycetaceae, Burkholderiales, and Spirochaetia were associated with lung cancer as previous sequencing studies did, along with other 16 significantly different species. The dysregulated functions in lung cancer microbiome were also explained in details. Our workflow provides improved efficiency in identification and characterization of the salivary microbiome with great reproducibility. The ability of enriching low-abundant bacteria and functions enables in-deep analysis of previously underestimated information.