scholarly journals Highly reproducible 16S sequencing facilitates measurement of host genetic influences on the stickleback gut microbiome

2018 ◽  
Author(s):  
Clayton M. Small ◽  
Mark Currey ◽  
Emily A. Beck ◽  
Susan Bassham ◽  
William A. Cresko
Keyword(s):  
Microbial Diversity ◽  
High Throughput ◽  
Gut Microbiome ◽  
Dna Isolation ◽  
Minor Effect ◽  
Tissue Preparation ◽  
Host Genotype ◽  
16S Sequencing ◽  
Host Microbe Interactions ◽  
Microbiome Data

AbstractMulticellular organisms interact with resident microbes in important ways, and a better understanding of host-microbe interactions is aided by tools such as high-throughput 16S sequencing. However, rigorous evaluation of the veracity of these tools in a different context from which they were developed has often lagged behind. Our goal was to perform one such critical test by examining how variation in tissue preparation and DNA isolation could affect inferences about gut microbiome variation between two genetically divergent lines of threespine stickleback fish maintained in the same lab environment. Using careful experimental design and intensive sampling of individuals, we addressed technical and biological sources of variation in 16S-based estimates of microbial diversity. After employing a two-tiered bead beating approach consisting of tissue homogenization followed by microbial lysis in subsamples, we found an extremely minor effect of DNA isolation protocol relative to among-host microbial diversity differences. Individual abundance estimates for rare OTUs, however, showed much lower reproducibility. We found that the stickleback gut microbiome was highly variable, even among siblings housed together, but that an effect of host genotype (stickleback lineage) was detectable for some microbial taxa. Our findings demonstrate the importance of appropriately quantifying biological and technical variance components when attempting to understand major influences on high-throughput microbiome data.

scholarly journals Highly Reproducible 16S Sequencing Facilitates Measurement of Host Genetic Influences on the Stickleback Gut Microbiome

mSystems ◽  
2019 ◽  
Vol 4 (4) ◽  
Author(s):  
Clayton M. Small ◽  
Mark Currey ◽  
Emily A. Beck ◽  
Susan Bassham ◽  
William A. Cresko
Keyword(s):  
Microbial Diversity ◽  
High Throughput ◽  
Gut Microbiome ◽  
Dna Isolation ◽  
Minor Effect ◽  
Tissue Preparation ◽  
Host Genotype ◽  
16S Sequencing ◽  
Microbiome Composition ◽  
Host Microbe Interactions

ABSTRACT Multicellular organisms interact with resident microbes in important ways, and a better understanding of host-microbe interactions is aided by tools such as high-throughput 16S sequencing. However, rigorous evaluation of the veracity of these tools in a different context from which they were developed has often lagged behind. Our goal was to perform one such critical test by examining how variation in tissue preparation and DNA isolation could affect inferences about gut microbiome variation between two genetically divergent lines of threespine stickleback fish maintained in the same laboratory environment. Using careful experimental design and intensive sampling of individuals, we addressed technical and biological sources of variation in 16S-based estimates of microbial diversity. After employing a two-tiered bead beating approach that comprised tissue homogenization followed by microbial lysis in subsamples, we found an extremely minor effect of DNA isolation protocol relative to among-host microbial diversity differences. Abundance estimates for rare operational taxonomic units (OTUs), however, showed much lower reproducibility. Gut microbiome composition was highly variable across fish—even among cohoused siblings—relative to technical replicates, but a subtle effect of host genotype (stickleback line) was nevertheless detected for some microbial taxa. IMPORTANCE Our findings demonstrate the importance of appropriately quantifying biological and technical variance components when attempting to understand major influences on high-throughput microbiome data. Our focus was on understanding among-host (biological) variance in community metrics and its magnitude in relation to within-host (technical) variance, because meaningful comparisons among individuals are necessary in addressing major questions in host-microbe ecology and evolution, such as heritability of the microbiome. Our study design and insights should provide a useful example for others desiring to quantify microbiome variation at biological levels in the face of various technical factors in a variety of systems.

scholarly journals Gut microbiome stability and resilience: elucidating the response to perturbations in order to modulate gut health

Gut ◽  
2020 ◽  
pp. gutjnl-2020-321747
Author(s):  
Marina Fassarella ◽  
Ellen E Blaak ◽  
John Penders ◽  
Arjen Nauta ◽  
Hauke Smidt ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Microbial Diversity ◽  
Gut Microbiome ◽  
Gut Health ◽  
Stable States ◽  
Host Genotype ◽  
Functional Richness ◽  
Microbe Interactions ◽  
Host Microbe Interactions ◽  
Stability And Resilience

The human gut microbiome is a complex ecosystem, densely colonised by thousands of microbial species. It varies among individuals and depends on host genotype and environmental factors, such as diet and antibiotics. In this review, we focus on stability and resilience as essential ecological characteristics of the gut microbiome and its relevance for human health. Microbial diversity, metabolic flexibility, functional redundancy, microbe–microbe and host–microbe interactions seem to be critical for maintaining resilience. The equilibrium of the gut ecosystem can be disrupted by perturbations, such as antibiotic therapy, causing significant decreases in functional richness and microbial diversity as well as impacting metabolic health. As a consequence, unbalanced states or even unhealthy stable states can develop, potentially leading to or supporting diseases. Accordingly, strategies have been developed to manipulate the gut microbiome in order to prevent or revert unhealthy states caused by perturbations, including faecal microbiota transplantation, supplementation with probiotics or non-digestible carbohydrates, and more extensive dietary modifications. Nevertheless, an increasing number of studies has evidenced interindividual variability in extent and direction of response to diet and perturbations, which has been attributed to the unique characteristics of each individual’s microbiome. From a clinical, translational perspective, the ability to improve resilience of the gut microbial ecosystem prior to perturbations, or to restore its equilibrium afterwards, would offer significant benefits. To be effective, this therapeutic approach will likely need a personalised or subgroup-based understanding of individual genetics, diet, gut microbiome and other environmental factors that might be involved.

scholarly journals Harnessing Colon Chip Technology to Identify Commensal Bacteria That Promote Host Tolerance to Infection

2021 ◽  
Vol 11 ◽  
Author(s):  
Francesca S. Gazzaniga ◽  
Diogo M. Camacho ◽  
Meng Wu ◽  
Matheus F. Silva Palazzo ◽  
Alexandre L. M. Dinis ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Human Microbiome ◽  
Commensal Bacteria ◽  
Bacterial Strains ◽  
Mucus Production ◽  
16S Sequencing ◽  
Chip Technology ◽  
Host Microbe Interactions ◽  
Host Tolerance

Commensal bacteria within the gut microbiome contribute to development of host tolerance to infection, however, identifying specific microbes responsible for this response is difficult. Here we describe methods for developing microfluidic organ-on-a-chip models of small and large intestine lined with epithelial cells isolated from duodenal, jejunal, ileal, or colon organoids derived from wild type or transgenic mice. To focus on host-microbiome interactions, we carried out studies with the mouse Colon Chip and demonstrated that it can support co-culture with living gut microbiome and enable assessment of effects on epithelial adhesion, tight junctions, barrier function, mucus production, and cytokine release. Moreover, infection of the Colon Chips with the pathogenic bacterium, Salmonella typhimurium, resulted in epithelial detachment, decreased tight junction staining, and increased release of chemokines (CXCL1, CXCL2, and CCL20) that closely mimicked changes previously seen in mice. Symbiosis between microbiome bacteria and the intestinal epithelium was also recapitulated by populating Colon Chips with complex living mouse or human microbiome. By taking advantage of differences in the composition between complex microbiome samples cultured on each chip using 16s sequencing, we were able to identify Enterococcus faecium as a positive contributor to host tolerance, confirming past findings obtained in mouse experiments. Thus, mouse Intestine Chips may represent new experimental in vitro platforms for identifying particular bacterial strains that modulate host response to pathogens, as well as for investigating the cellular and molecular basis of host-microbe interactions.

scholarly journals Aggregating Knockoffs for False Discovery Rate Control with an Application to Gut Microbiome Data

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 230
Author(s):  
Fang Xie ◽  
Johannes Lederer
Keyword(s):  
Microbial Diversity ◽  
Rate Control ◽  
Gut Microbiome ◽  
High Dimensional ◽  
Health And Wellbeing ◽  
False Discovery ◽  
Recent Approach ◽  
Lasso Estimator ◽  
Microbiome Data ◽  
False Discoveries

Recent discoveries suggest that our gut microbiome plays an important role in our health and wellbeing. However, the gut microbiome data are intricate; for example, the microbial diversity in the gut makes the data high-dimensional. While there are dedicated high-dimensional methods, such as the lasso estimator, they always come with the risk of false discoveries. Knockoffs are a recent approach to control the number of false discoveries. In this paper, we show that knockoffs can be aggregated to increase power while retaining sharp control over the false discoveries. We support our method both in theory and simulations, and we show that it can lead to new discoveries on microbiome data from the American Gut Project. In particular, our results indicate that several phyla that have been overlooked so far are associated with obesity.

scholarly journals Harnessing Colon Chip technology to identify commensal bacteria that promote host tolerance to infection

2020 ◽  
Author(s):  
Francesca S. Gazzaniga ◽  
Diogo M. Camacho ◽  
Meng Wu ◽  
Matheus Palazzo ◽  
Alexandre Dinis ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Human Microbiome ◽  
Commensal Bacteria ◽  
Bacterial Strains ◽  
Mucus Production ◽  
16S Sequencing ◽  
Chip Technology ◽  
Host Microbe Interactions ◽  
Host Tolerance

ABSTRACTCommensal bacteria within the gut microbiome contribute to development of host tolerance to infection, however, identifying specific microbes responsible for this response is difficult. Here we describe methods for developing microfluidic organ-on-a-chip models of small and large intestine lined with epithelial cells isolated from duodenal, jejunal, ileal, or colon organoids derived from wild type or transgenic mice. To focus on host-microbiome interactions, we carried out studies with the mouse Colon Chip and demonstrated that it can support co-culture with living gut microbiome and enable assessment of effects on epithelial adhesion, tight junctions, barrier function, mucus production, and cytokine release. Moreover, infection of the Colon Chips with the pathogenic bacterium, Salmonella typhimurium, resulted in epithelial detachment, decreased tight junction staining, and increased release of cytokines (CXCL1, CXCL2, and CCL20) that closely mimicked changes previously seen in mice. Symbiosis between microbiome bacteria and the intestinal epithelium was also recapitulated by populating Colon Chips with complex living mouse or human microbiome. By taking advantage of differences in the composition between complex microbiome samples cultured on each chip using 16s sequencing, we were able to identify Enterococcus faecium as a positive contributor to host tolerance, confirming past findings obtained in mouse experiments. Thus, mouse Intestine Chips may represent new experimental in vitro platforms for identifying particular bacterial strains that modulate host response to pathogens, as well as for investigating the cellular and molecular basis of host-microbe interactions.

scholarly journals Endocannabinoid system mediates the association between gut-microbial diversity and anhedonia/amotivation in a general population cohort

2021 ◽  
Author(s):  
Amedeo Minichino ◽  
Matthew A. Jackson ◽  
Marta Francesconi ◽  
Claire J. Steves ◽  
Cristina Menni ◽  
...  
Keyword(s):  
General Population ◽  
Microbial Diversity ◽  
Gut Microbiome ◽  
Endocannabinoid System ◽  
Alpha Diversity ◽  
Serum Levels ◽  
Population Cohort ◽  
Random Intercept ◽  
General Population Cohort ◽  
Antidepressant Use

AbstractAnhedonia and amotivation are debilitating symptoms and represent unmet therapeutic needs in a range of clinical conditions. The gut-microbiome-endocannabinoid axis might represent a potential modifiable target for interventions. Based on results obtained from animal models, we tested the hypothesis that the endocannabinoid system mediates the association between gut-microbiome diversity and anhedonia/amotivation in a general population cohort. We used longitudinal data collected from 786 volunteer twins recruited as part the TwinsUK register. Our hypothesis was tested with a multilevel mediation model using family structure as random intercept. The model was set using alpha diversity (within-individual gut-microbial diversity) as predictor, serum and faecal levels of the endocannabinoid palmitoylethanolamide (PEA) as mediator, and anhedonia/amotivation as outcome. PEA is considered the endogenous equivalent of cannabidiol, with increased serum levels believed to have anti-depressive effects, while increased stool PEA levels, reflecting increased excretion, are believed to have opposite, detrimental, effects on mental health. We therefore expected that either reduced serum PEA or increased stool PEA would mediate the association between microbial diversity and anhedonia amotivation. Analyses were adjusted for obesity, diet, antidepressant use, sociodemographic and technical covariates. Data were imputed using multiple imputation by chained equations. Mean age was 65.2 ± 7.6; 93% of the sample were females. We found a direct, significant, association between alpha diversity and anhedonia/amotivation (β = −0.37; 95%CI: −0.71 to −0.03; P = 0.03). Faecal, but not serum, levels of the endocannabinoid palmitoylethanolamide (PEA) mediated this association: the indirect effect was significant (β = −0.13; 95%CI: −0.24 to −0.01; P = 0.03), as was the total effect (β = −0.38; 95%CI: −0.72 to −0.04; P = 0.03), whereas the direct effect of alpha diversity on anhedonia/amotivation was attenuated fully (β = −0.25; 95%CI: −0.60 to 0.09; P = 0.16). Our results suggest that gut-microbial diversity might contribute to anhedonia/amotivation via the endocannabinoid system. These findings shed light on the biological underpinnings of anhedonia/amotivation and suggest the gut microbiota-endocannabinoid axis as a promising therapeutic target in an area of unmet clinical need.

scholarly journals Environmental Sequencing Provides Reasonable Estimates of the Relative Abundance of Specific Picoeukaryotes

2016 ◽  
Vol 82 (15) ◽  
pp. 4757-4766 ◽  
Author(s):  
Caterina R. Giner ◽  
Irene Forn ◽  
Sarah Romac ◽  
Ramiro Logares ◽  
Colomban de Vargas ◽  
...  
Keyword(s):  
Microbial Diversity ◽  
High Throughput ◽  
Relative Abundance ◽  
Ribosomal Dna ◽  
18S Rdna ◽  
High Throughput Sequencing ◽  
454 Sequencing ◽  
Epifluorescence Microscopy ◽  
Environmental Sequencing

ABSTRACTHigh-throughput sequencing (HTS) is revolutionizing environmental surveys of microbial diversity in the three domains of life by providing detailed information on which taxa are present in microbial assemblages. However, it is still unclear how the relative abundance of specific taxa gathered by HTS correlates with cell abundances. Here, we quantified the relative cell abundance of 6 picoeukaryotic taxa in 13 planktonic samples from 6 European coastal sites using epifluorescence microscopy on tyramide signal amplification-fluorescencein situhybridization preparations. These relative abundance values were then compared with HTS data obtained in three separate molecular surveys: 454 sequencing of the V4 region of the 18S ribosomal DNA (rDNA) using DNA and RNA extracts (DNA-V4 and cDNA-V4) and Illumina sequencing of the V9 region (cDNA-V9). The microscopic and molecular signals were generally correlated, indicating that a relative increase in specific 18S rDNA was the result of a large proportion of cells in the given taxa. Despite these positive correlations, the slopes often deviated from 1, precluding a direct translation of sequences to cells. Our data highlighted clear differences depending on the nucleic acid template or the 18S rDNA region targeted. Thus, the molecular signal obtained using cDNA templates was always closer to relative cell abundances, while the V4 and V9 regions gave better results depending on the taxa. Our data support the quantitative use of HTS data but warn about considering it as a direct proxy of cell abundances.IMPORTANCEDirect studies on marine picoeukaryotes by epifluorescence microscopy are problematic due to the lack of morphological features and due to the limited number and poor resolution of specific phylogenetic probes used in fluorescencein situhybridization (FISH) routines. As a consequence, there is an increasing use of molecular methods, including high-throughput sequencing (HTS), to study marine microbial diversity. HTS can provide a detailed picture of the taxa present in a community and can reveal diversity not evident using other methods, but it is still unclear what the meaning of the sequence abundance in a given taxon is. Our aim is to investigate the correspondence between the relative HTS signal and relative cell abundances in selected picoeukaryotic taxa. Environmental sequencing provides reasonable estimates of the relative abundance of specific taxa. Better results are obtained when using RNA extracts as the templates, while the region of 18S ribosomal DNA had different influences depending on the taxa assayed.

Utilizing the Microbiota and Machine Learning Algorithms to Assess Risk of Salmonella Contamination in Poultry Rinsate

2021 ◽  
Author(s):  
Hannah Bolinger ◽  
David Tran ◽  
Kenneth Harary ◽  
George C. Paoli ◽  
Giselle Guron ◽  
...  
Keyword(s):  
Machine Learning ◽  
Machine Learning Algorithms ◽  
Diagnostic Tools ◽  
Sequencing Data ◽  
Testing Methods ◽  
16S Sequencing ◽  
Sequencing Technologies ◽  
Microbiological Testing ◽  
Microbiome Data ◽  
Larger Sample

Traditional microbiological testing methods are slow, and many molecular-based techniques rely on culture-based enrichment to overcome low limits of detection. Recent advancements in sequencing technologies may make it possible to utilize machine learning (ML) to identify patterns in microbiome data to potentially predict the presence or absence of pathogens. In this study, 299 poultry rinsate samples from various points in the processing chain were analyzed to determine if microbiota could inform about a sample’s risk for containing Salmonella . Samples were culture confirmed as Salmonella -positive or -negative following modified USDA MLG protocols. The culture confirmation result was used as a reference to compare with 16S sequencing data. Pre-chill samples tested positive (71/82) at a higher frequency than post-chill samples (30/217) and contained greater microbial diversity. Due to their larger sample size, post-chill samples were analyzed more deeply. Analysis of variance (ANOVA) identified a significant effect of chilling on the number of genera (p<0.001), but analysis of similarities (ANOSIM) failed to provide evidence for microbial dissimilarity between pre- and post-chill samples (p=0.001, R=0.443). Various ML models were trained using post-chill samples to predict if a sample contained Salmonella based on the samples’ microbiota pre-enrichment. The optimal model was a Random Forest-based model with a performance as follows: accuracy (88%), sensitivity (85%), specificity (90%). While the algorithms described in this paper are prototypes, these risk-based algorithms demonstrate the potential and need for further studies to provide insight alongside diagnostic tests. Combining risk-based information with diagnostic tools can help poultry processors make informed decisions to help identify and prevent the spread of Salmonella . These data add to the growing body of literature exploring novel ways to utilize microbiome data for predictive food safety.

scholarly journals Ear wound healing in MRL/MpJ mice is associated with gut microbiome composition and is transferable to non-healer mice via microbiome transplantation

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0248322
Author(s):  
Cassandra Velasco ◽  
Christopher Dunn ◽  
Cassandra Sturdy ◽  
Vladislav Izda ◽  
Jake Martin ◽  
...  
Keyword(s):  
Tissue Regeneration ◽  
Gut Microbiome ◽  
Vehicle Control ◽  
Repair Capacity ◽  
16S Sequencing ◽  
Microbiome Composition ◽  
Sex Effects ◽  
Elastic Cartilage ◽  
Better Than ◽  
Hole Closure

Objective Adult elastic cartilage has limited repair capacity. MRL/MpJ (MRL) mice, by contrast, are capable of spontaneously healing ear punctures. This study was undertaken to characterize microbiome differences between healer and non-healer mice and to evaluate whether this healing phenotype can be transferred via gut microbiome transplantation. Methods We orally transplanted C57BL/6J (B6) mice with MRL/MpJ cecal contents at weaning and as adults (n = 57) and measured ear hole closure 4 weeks after a 2.0mm punch and compared to vehicle-transplanted MRL and B6 (n = 25) and B6-transplanted MRL (n = 20) mice. Sex effects, timing of transplant relative to earpunch, and transgenerational heritability were evaluated. In a subset (n = 58), cecal microbiomes were profiled by 16S sequencing and compared to ear hole closure. Microbial metagenomes were imputed using PICRUSt. Results Transplantation of B6 mice with MRL microbiota, either in weanlings or adults, improved ear hole closure. B6-vehicle mice healed ear hole punches poorly (0.25±0.03mm, mm ear hole healing 4 weeks after a 2mm ear hole punch [2.0mm—final ear hole size], mean±SEM), whereas MRL-vehicle mice healed well (1.4±0.1mm). MRL-transplanted B6 mice healed roughly three times as well as B6-vehicle mice, and half as well as MRL-vehicle mice (0.74±0.05mm, P = 6.9E-10 vs. B6-vehicle, P = 5.2E-12 vs. MRL-vehicle). Transplantation of MRL mice with B6 cecal material did not reduce MRL healing (B6-transplanted MRL 1.3±0.1 vs. MRL-vehicle 1.4±0.1, p = 0.36). Transplantation prior to ear punch was associated with the greatest ear hole closure. Offspring of transplanted mice healed significantly better than non-transplanted control mice (offspring:0.63±0.03mm, mean±SEM vs. B6-vehicle control:0.25±0.03mm, n = 39 offspring, P = 4.6E-11). Several microbiome clades were correlated with healing, including Firmicutes (R = 0.84, P = 8.0E-7), Lactobacillales (R = 0.65, P = 1.1E-3), and Verrucomicrobia (R = -0.80, P = 9.2E-6). Females of all groups tended to heal better than males (B6-vehicle P = 0.059, MRL-transplanted B6 P = 0.096, offspring of MRL-transplanted B6 P = 0.0038, B6-transplanted MRL P = 1.6E-6, MRL-vehicle P = 0.0031). Many clades characteristic of female mouse cecal microbiota vs. males were the same as clades characteristic of MRL and MRL-transplanted B6 mice vs. B6 controls, including including increases in Clostridia and reductions in Verrucomicrobia in female mice. Conclusion In this study, we found an association between the microbiome and tissue regeneration in MRL mice and demonstrate that this trait can be transferred to non-healer mice via microbiome transplantation. We identified several microbiome clades associated with healing.

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