Species Genus And Cluster Level Analyses Are Complementary
Species-level testing can capture the signals that are lost at genus level due heterogeneity within genus. In fact, we detected associations with 22 species belonging to 12 genera where the associations were missed at genus-level MWAS . Conversely, when species are rare and excluded from testing for statistical reasons, the signal may be present at genus level due to cumulative effects of species with similar effects . Networks of correlating species is another complimentary source of information as it may reveal disease-relevant polymicrobial clusters. Consider cluster #17 composed of 19 opportunistic pathogen species from 10 genera: species-level MWAS detected only one of the 19 species as elevated in PD , genus-level MWAS detected 3 of the 10 genera as elevated in PD , and cluster-level analysis detected the whole polymicrobial cluster as elevated in PD.
The Mechanism Of Tcm In Regulating Pd Is Mediated Via The Gut Microbiota
Gut microbiota play an important role in the occurrence and development of PD. TCM protects the intestinal mucosal barrier, and restores the diversity of intestinal microbes by regulating the amount and proportion of gut microbiota and metabolites, which not only can decrease release of pro-inflammatory cytokines from the gut into the bloodstream, but also increase the level of SCFAs and certain neuroactive factors, that exerts anti-oxidative, anti-inflammatory, anti-apoptotic via neuronal mechanism, endocrine mechanism, and immunological mechanism.57,58 This in turn can protect dopamine neurons in the brain and prevent the development of PD.
How Your Support Made This Research Project Possible
Appel-Cresswells new project builds on earlier research to study the fungal microbiome, a project Parkinson Canada supported. That was one of the grants that then facilitated a whole lot more work, she says.
Its really the seed funding, particularly with these pilot grants, that allows us to go way beyond that. Its the necessary start to any of these projects.
Seed or pilot grants allow researchers to leverage funding from other sources.
You have to start somewhere, and that is the seed that is planted and has really grown into a whole program that is very interconnected and makes use of all these synergies between all these fields, she says.
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Intestinal Inflammation And Barrier Dysfunction
The intestinal mucosa is the inner lining of the GI tract. It is a physical and an immunological barrier between the environment and the internal host environs blood circulation, which is semipermeable and essential in the uptake of nutrients. It consists of an outer mucosal layer, a middle epithelial layer, and an inner lamina propria. The mucosal layer overlaying the epithelium is in close proximity to the external environment, communicates with gut microbiota, and keeps a check on pathogenic bacteria with immune sensing antimicrobial peptides and secretory IgA. A monolayer of epithelial cells with tight junction and adherens junction transport molecules and maintain the barriers integrity, respectively. Immune cells such as T-cells, B-cells, macrophages, and dendritic cells are in the lamina propria forming a defence barrier .
Parkinsons Disease: Origins In The Gut
To Hafler, a leading researcher in multiple sclerosis, this gut-brain connection was not a total surprise. One of the main treatments for MS, Tysabri, works by targeting a homing receptor that is shared only between the brain and gut. Now, he and his colleagues are focusing on Parkinsons disease, whose possible origins in the gut are backed up by emerging, convincing evidence.
Patients with neurodegenerative diseases such as MS or Parkinsons exhibit differences in their microbiomes, but researchers dont yet understand why this happens. An intriguing observation scientists have made about Parkinsons disease, for instance, is that early symptoms can include dysfunction of the gut, usually resulting in constipation. The dysfunction of the nervous system that regulates gut function actually precedes the onset of Parkinsons disease, sometimes by decades, says Palm.
Hafler hopes his teams findings will prepare him to create a clinical trial focused on treating patients with Parkinsons. One of the major obstacles in treating autoimmune disease is that a drug that helps one condition may trigger a different one. He believes that a more in-depth knowledge of the inflammatory nature of Parkinsons will help him design a stronger trial.
Rather than conducting a clinical trial blindly, I want to better understand the nature of the inflammatory insult to better target the immune system, he says.
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Gut Microbiota Associated With Pd
Studies on the gut microbiome of PD have been carried out on diverse populations worldwide by following different protocols, most of which are casecontrol studies, a few are follow-up studies, some target a specific group of organisms, some others deal with shotgun metagenomics, and most of the others have employed 16S rRNA sequencing . Various studies have analysed the relative abundance of bacterial taxa in PD and compared it with healthy controls using diverse platforms and databases. This review focuses on the intraluminal microbiome encountered in faecal samples of PD compared to HC, as stated in Table 1. Putative cellulose-degrading bacterial taxa Prevotellaceae , Ruminococcaceae , Lachnospiraceae that produce SCFA and help in the synthesis of mucin to maintain the intestinal integrity are considerably lower in abundance in PD . On the contrary, a few putative pathobionts of the family Enterobacteriaceae, Enterococcaceae, which are assumed to possibly reduce the production of SCFA, produce endotoxins and neurotoxins that promote intestinal inflammation, are enriched in PD . An altered microbial composition, a decrease in bacteria associated with SCFA synthesis that is bacteria related to anti-inflammation, and a higher abundance of proinflammatory pathobionts of phylum Proteobacteria in PD, are similar to that of the changes observed in IBD .
Western Blotting Spectrophotometry And Elisa Determinations In Brain Intestine Homogenates And Blood
After completing the behavioural tests, Unt and BMAA-treated mice were euthanised and blood, mesencephalon, striatum, ileum and cecum samples were isolated. Tissues were snap frozen, stored at 80°C and homogenised as described in . Plasma interferon and IL-6 levels were determined. In mesencephalic homogenates we determined synaptic markers and innate immunity markers by western blot, caspase-1 activity by spectrophotometry and innate immunity markers and aSyn oligomers with ELISA kits and western blot. In striatal homogenates we determined dopamine levels with ELISA Kit. In ileum and cecum homogenates we determined caspase-1 activity by spectrophotometry, and innate immunity markers and aSyn oligomers with ELISA kits and by western blot .
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How Is The Microbiome Different In People With Pd
Based on numerous studies comparing the microbiome from the gut of people with PD with the microbiome from the gut of people without PD, there appear to be some differences. The studies are not consistent in their findings, but there are similarities across studies. These include an increase in certain families of bacteria such as Lactobacillaceae and Verrucomicrobiaceae, and a decrease in the family Prevotellaceae.
Richness And Evenness Were Altered Neither In Parkinsons Disease Patients Nor In Ms Patients In Comparison With Controls
For richness, we performed a weighting inverse variance meta-analysis with a random model. For each study, the SMD was estimated and reported on a Forest Plot with its confidence interval . We have also drawn distribution of diversity values for Parkinsons disease studies and MS . The overall estimate was not significant for both diseases . The highest change in richness was observed for Keshavarzian et al., confirming results reported in this publication. We also adjusted SMD estimates for age and sex, two confounding factors. This adjustment was done for Parkinsons disease studies only, but richness was still not altered in patients in comparison with donors .
Distribution of richness values for each study, stratified by disease groups . Distribution of evenness values for each study, stratified by disease groups Distribution of Shannon values for each study, stratified by disease groups .
We performed the same analysis for evenness. Evenness was non-significantly decreased in Parkinsons disease with an overall estimate at 0.17 , neither in MS . For Parkinsons disease, the evenness was decreased in five studies, and increased in only two studies . After adjustment for age and sex, the overall estimate was still not significant for Parkinsons disease studies , but the number of studies included into the meta-analysis was reduced to four.
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The Triangle Of Coffee Gut Motility And Microbiota Is It Relevant For Gut Dysfunction In Pd
Regarding coffee the best documented effects on the gastrointestinal tract are promotion of gastro-oesophageal reflux, stimulation of gallbladder contraction and an increase of colonic motor activity . Distal colonic motility increases as early as 4 minutes after coffee ingestion . These effects are unlikely mediated by caffeine, instead an indirect action on the colon mediated by neural mechanisms or gastrointestinal hormones has been suspected. Coffee consumption is also inversely associated with the prevalence of self-reported constipation . Some effects of coffee might be related to constituents such as alkaloids, phenolic compounds, fibers, and minerals.Dietary fiber contained in coffee has marked effects on gut microbiota. It is rapidly metabolized intoSCFAs and causes a marked expansion of Bacteroides/Prevotella bacteria . In vivo, one study found a decrease of Bacteroides after coffee consumption while another did not find changes of Bacteroides/Prevotella . This could, however, indicate an expansion of Prevotella bacteria since their abundance is inversely associated with that of Bacteroides . In vivo, coffee caused an increase of anti-inflammatory Bifidobacteria and a decrease of Clostridium spp. and Escherichia coli that invade the gut mucosa in PD.
Subject Characteristics And Metadata
Data on 53 variables were analyzed to characterize the subjects, and to identify disease-associated variables that could potentially confound downstream metagenomics analyses . GI problems, which are well-known features of PD, were readily evident in this cohort. Constipation was more prevalent in PD cases =6.1, 95% confidence interval =3.910, P=2E19 for chronic constipation, P=3E6 for Bristol Chart score), and PD cases reported more GI discomfort than NHC . Compared to NHC, PD cases had diminished intake of alcohol and foods in all five categories , all reaching significance except grains . Use of laxatives , pain medication , sleep aid , and medication for depression/anxiety/mood were more common in PD than NHC. Probiotic supplement use was more common in NHC than PD , which is noteworthy because as the data will show, Bifidobacterium and Lactobacillus species, which are common constituents of commercial probiotics, were more abundant in PD than NHC metagenomes. Variables that differed in PD vs. NHC were evaluated as potential confounders in downstream metagenomics analyses.
Table 1 Subject characteristics and metadata
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Data Retrieval And Zotu Picking
Raw reads were downloaded from SRA or the European Nucleotide Archive . Adapters were removed using the bbtools suit. Data were analyzed using Lotus and the UNOISE3 algorithm for zOTUs calculation, bundled in a new Lotus version , currently under development. Due to the technical variability among datasets the filtering parameters used by the sdm program called by Lotus, were adjusted for each dataset independently and are reported in the supplementary materials . For the datasets of Petrov et al. and Weis et al., we had to decrease the accepted minimum error due to the low quality of the sequencing data . 16S-based functional predictions were obtained using the default settings in picrust2 and the Metacyc database. In this analysis, the dataset of Qian et al. was not included, as with the default cutoffs the sequences aligned poorly with the reference database used. Count tables for species, genera, families, and functional predictions were then analyzed using R v3.6.2 and processed using the phyloseq R package. We then retained all samples with > 4500 reads, as well as taxa with > 5 counts and predicted functionalities with > 20 counts in at least 2.5% of the samples. These filtration steps left a total of 1211 and 1121 samples for the taxonomic and predicted-function data, respectively. Enterotypes were predicted using rarefied relative abundances of genera via the web-platform.
Alterations In The Gut Microbiota Between Parkinsons Disease And Household Control Cohorts
Comparison of the mean relative abundance at the genus and family levels for the 74 individual PD patients and 74 HC at baseline, 6 and 12 months are presented in Figure 1A and Supplementary Figure 3. Statistically significant relative abundance differences were noted between the PD and HC groups at genus, family, order and phylum taxonomic levels across the three-time intervals .
Figure 1. Alterations in the gut microbiota between the Parkinsons disease and household control cohorts. Individual participant mean relative abundance differences for the PD and HC groups at genus and family taxonomic levels at 0, 6, and 12 months intervals, were statistically different between the groups . Alpha-diversity at the Amplicon Specific Variant level for PD and HC participants across 0, 6, and 12 months intervals, showed significant alpha-diversity differences between the groups . Beta-diversity explored by Principal Component Analysis with BrayCurtis ordination at the ASV level was averaged for each participant and presented as a sphere relative to the variability of the diversity measure across the three time intervals. A statistically significant difference in beta diversity was noted between the two groups .
Exploration of Composition Differences for Indicator Taxa
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Gut Microbiome And Metabolic Changes In Parkinsons Disease
With increased accessibility to next-generation sequencing technologies, there has been an expansion of studies showing significant, albeit varying, differences in the gut microbiome in PD compared to non-PD controls. These have recently been reviewed by Lubomski et al., ,
Interestingly, several 16S rRNA gene-sequencing studies have shown significantly reduced abundances of butyrate-producing bacteria in PD fecal samples compared to controls.- These findings were supported by a quantitative real-time polymerase chain reaction study targeting butyrate synthesis genes and a gas chromatography study demonstrating significantly reduced fecal levels of short-chain fatty acids in PD patients versus controls. SCFAs are thought to play a key role in microbiotaÃ¢gutÃ¢brain crosstalk, in part via the regulation of bloodÃ¢brain barrier integrity, neuronal survival, inflammatory cascades, and endocrine signaling. Butyrate in particular is a major energy substrate for the colonic epithelium and acts to improve gut barrier function. Being a histone deacetylase inhibitor , butyrate has been found to exert neuroprotective actions in experimental PD models,, including the mitigation of PD motor impairment and dopaminergic cell death.-
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Stool Dna Extraction And 16s Ribosomal Rna Amplicon Sequencing
Stool samples were snap frozen upon receipt, with total fecal DNA isolated within 2 months of receiving stool samples. DNA was extracted using an optimized protocol for the MP Biomedicals FastDNA SPIN Kit for Feces . DNA integrity was confirmed by polymerase chain reaction using universal primers to the V3V4 regions and whole genome of bacterial 16S ribosomal DNA .
16S rRNA V3-V4 amplicon sequencing was performed by the Ramaciotti Centre for Genomics . Sequencing libraries were generated using standard V3V4 primers and a two-stage amplicon and indexing PCR with KAPA HiFi polymerase to generate 300 bp paired-end reads. Libraries were cleaned up after each PCR using Ampure XP beads and normalized using the Applied Biosciences SequalPrep Plate Normalization kit . Sequencing was performed on an Illumina MiSeq platform using MiSeq v3 chemistry with PhiX control v3. Internal sequencing controls included replicate patient stool DNA samples and the ZymoBIOMICS Microbial Community DNA Standard for validation of sequencing batches.
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This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License . Usage and distribution for commercial purposes requires written permission. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor. The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.
How Might An Altered Microbiome Contribute To Pd Pathology
These studies beg the question how might the gut microbiome contribute to PD pathology in the brain? Several different theories have been proposed:
- Short chain fatty acids are one of the main products of the microbiome. Research has shown that SCFAs can enter the brain and exert neuroprotective effects via increase of nerve growth factors. A number of research studies have shown that there are less SCFAs in fecal samples from people with PD as compared to healthy controls and this could contribute to a lack of neuroprotection that then fuels PD.
- Gherlin is a neuropeptide that stimulates appetite and might have neuroprotective effects. It has been shown that levels of gherlin are lower in people with PD than healthy controls. In addition, research has shown that blood levels of gherlin may depend on the gut microbiome and could therefore be an additional factor that connects PD and the gut microbiome.
- A PD microbiome may release pro-inflammatory molecules such as TNF-alpha and interferon-gamma which can enter the brain. These pro-inflammatory molecules may contribute to PD pathology.
- A PD microbiome may increase the ability of molecules to permeate the intestinal wall. This may allow neurotoxins to enter the gut.
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