The immune response to Prevotella bacteria in chronic inflammatory disease

Immunology, Год журнала: 2017, Номер 151(4), С. 363 - 374

Опубликована: Май 23, 2017

The microbiota plays a central role in human health and disease by shaping immune development, responses metabolism, protecting from invading pathogens. Technical advances that allow comprehensive characterization of microbial communities genetic sequencing have sparked the hunt for disease-modulating bacteria. Emerging studies humans linked increased abundance Prevotella species at mucosal sites to localized systemic disease, including periodontitis, bacterial vaginosis, rheumatoid arthritis, metabolic disorders low-grade inflammation. Intriguingly, is reduced within lung patients with asthma chronic obstructive pulmonary disease. Increased associated augmented T helper type 17 (Th17) -mediated inflammation, which line marked capacity driving Th17 vitro. Studies indicate predominantly activate Toll-like receptor 2, leading production Th17-polarizing cytokines antigen-presenting cells, interleukin-23 (IL-23) IL-1. Furthermore, stimulate epithelial cells produce IL-8, IL-6 CCL20, can promote neutrophil recruitment. Prevotella-mediated inflammation leads dissemination inflammatory mediators, bacteria products, turn may affect outcomes. mice support causal as colonization experiments clinical features When compared strict commensal bacteria, exhibit properties, demonstrated release mediators various stromal cells. These findings some strains be clinically important pathobionts participate promoting

Язык: Английский

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1,520 reference genomes from cultivated human gut bacteria enable functional microbiome analyses

Nature Biotechnology, Год журнала: 2019, Номер 37(2), С. 179 - 185

Опубликована: Фев. 1, 2019

Язык: Английский

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Prevotella diversity, niches and interactions with the human host

Nature Reviews Microbiology, Год журнала: 2021, Номер 19(9), С. 585 - 599

Опубликована: Май 28, 2021

Язык: Английский

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Microbial regulation of organismal energy homeostasis

Nature Metabolism, Год журнала: 2018, Номер 1(1), С. 34 - 46

Опубликована: Дек. 30, 2018

Язык: Английский

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Deciphering microbial interactions in synthetic human gut microbiome communities

Molecular Systems Biology, Год журнала: 2018, Номер 14(6)

Опубликована: Июнь 1, 2018

Article21 June 2018Open Access Transparent process Deciphering microbial interactions in synthetic human gut microbiome communities Ophelia S Venturelli Corresponding Author [email protected] orcid.org/0000-0003-2200-1963 Department of Biochemistry, University Wisconsin-Madison, Madison, WI, USA Search for more papers by this author Alex V Carr Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, Garth Fisher Ryan H Hsu orcid.org/0000-0001-8221-224X California Institute Quantitative Biosciences, Rebecca Lau Benjamin P Bowen Susan Hromada Trent Northen Adam Arkin Bioengineering, Energy Biosciences Institute, Information *,1, Carr2,‡,‡, Fisher2,‡, Hsu3, Lau2, Bowen2, Hromada1, Northen2 Arkin2,3,4,5 1Department 2Environmental 3California 4Department 5Energy ‡These authors contributed equally to work ‡Correction added on 27 2018 after first online publication: C was corrected *Corresponding author. Tel: +1 608 263 7017; E-mail: Molecular Biology (2018)14:e8157https://doi.org/10.15252/msb.20178157 See also: Abreu et al (June 2018) PDFDownload PDF article text main figures. Peer ReviewDownload a summary the editorial decision including letters, reviewer comments responses feedback. ToolsAdd favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract The ecological forces that govern assembly stability microbiota remain unresolved. We developed generalizable model-guided framework predict higher-dimensional consortia from time-resolved measurements lower-order assemblages. This method employed decipher diverse community. show pairwise are major drivers multi-species community dynamics, as opposed higher-order interactions. inferred network exhibits high proportion negative frequent positive Ecological responsive recipient species were discovered network. Our model demonstrated prevalent interaction topology enables robust coexistence implementing feedback loop balances disparities monospecies fitness levels. could generate history-dependent initial proportions frequently do not originate bistability. Measurements extracellular metabolites illuminated metabolic capabilities potential molecular basis In sum, these methods defined roles human-associated intestinal design principles communities. Synopsis Analysis shows dynamics. study reveals drivers, metabolite hub ecologically sensitive organisms A data-driven pipeline is used construct predictive dynamic anaerobic Design stable history-dependence elucidated. profiles analyzed each organism. highlights challenges using phylogenetic exo-metabolomic "signals" functions. Introduction Microbes have evolved occupy nearly every environment Earth, spanning extreme environments such acid mine drains hot springs multicellular organisms. dense collection microorganisms inhabits gastrointestinal tract (Lozupone al, 2012; Earle 2015; Tropini 2017) performs numerous functions impact physiology, nutrition, behavior, development (Ley 2005; Fischbach Sonnenburg, 2011; Foster McVey Neufeld, 2013; Louis 2014; Sharon Rooks Garrett, 2016). Functions partitioned among genetically distinct populations interact perform complex chemical transformations exhibit emergent properties colonization resistance at level. Such collective realized combined operating multiple time spatial scales be achieved single population. degree structuring varies across length scales: At macroscale hundreds micrometers, bacteria cluster into habitats, whereas scale intermixing members has been observed (Donaldson Mark Welch 2017). composed bacterial species, majority which span Firmicutes, Bacteroidetes, Actinobacteria phyla 2006). Constituent strains shown persist an individual over long periods time, demonstrating (Faith 2013). Perturbations system dietary shifts or antibiotic administration can shift point alternative state (Relman, 2012). While identities co-occurrence relationships individuals elucidated (Faust 2012), we lack quantitative understanding how shape assembly, stability, response perturbations. For example, enable dominant Bacteroidetes well understood (Fischbach 2011). resilience microbiomes, capacity recover perturbations, strongly linked diversity. Indeed, reduction diversity associated with diseases, suggesting high-dimensional functionally heterogeneous ecosystem promotes health (Sommer Understanding factors influencing implications targeted interventions modulate states. Central problem inferring unknown developing tools temporal changes behaviors environmental stimuli. Cooperation competition feedbacks influence functional activities stability. Negative dominate inter-relationships aquatic microcosms (Foster Bell, However, prevalence cooperation occupying other remains elusive. Direct resources space, biomolecular warfare, production toxic waste products (Hibbing 2010). Positive stem secreted utilized member detoxification environment. Pairwise modified third organism, leading effects (Bairey driver large structure function, represent key nodes manipulated control states (Gibson Predicting dynamics step toward organizational Computational models different resolutions analyze Raes, Dynamic computational investigate structure, dynamical systems theory parameter sensitivity (Astrom Murray, Generalized Lotka–Volterra (gLV) ordinary differential equation represents limited number parameters deduced time-series data. Here, develop systematic modeling experimental interrogate mediating assembly. Time-resolved assemblages train revealed Specific context identified exhibited overall community, specific Firmicutes displayed outgoing sub-network variations parameters. showed due slow convergence steady composition networks enriched exo-metabolomics profiling, data pinpointed set predicted mediate failed forecast influential modulating Together, results combinations couplings realize repertoire behaviors. Results Probing aimed dissect reduced complexity Actinobacteria, Proteobacteria. To end, ecology encompassing Bacteroides thetaiotaomicron (BT), ovatus (BO), uniformis (BU), vulgatus (BV), Blautia hydrogenotrophica (BH), Collinsella aerofaciens (CA), Clostridium hiranonis (CH), Desulfovibrio piger (DP), Eggerthella lenta (EL), Eubacterium rectale (ER), Faecalibacterium prausnitzii (FP), Prevotella copri (PC) designed mirror natural (Fig 1A; Qin These contribute significantly implicated diseases (Watterlot 2008; Larsen 2010; Thota Fujimoto Haiser Scher Table 1). Figure 1. Experimental high-throughput characterization Phylogenetic tree 12-member analysis performed concatenated alignment single-copy marker genes obtained via PhyloSift (preprint: Darling 2014). Maximum likelihood trees generated default options. bar substitutions per site alignment. Schematic study. Species approximately 1:1 19:1 based absorbance 600 nm (OD600) microtiter plates liquid-handling robotic manipulation. Approximately 12 h, samples collected multiplexed 16S rRNA gene sequencing (black circles). Relative abundance measured V3–V4 region dual-indexed primers compatible Illumina platform (stacked plot, bottom right). Serial transfers 24 intervals (purple bars, top) transferring aliquot fresh media 1:20 dilution. parallel, OD600 performed. Download figure PowerPoint associations previous literature. Arrows pointing up down denote associations, respectively Association(s) Inflammatory autoimmune disease (↑) (Scher 2013), autism (↓) (Kang 2013) (BV) Ulcerative colitis (Bamba 1995) (BU) Metabolic/immunological dysfunction (Gauffin Cano 2012) (BO) Type I diabetes (Giongo 2011) (BT) (↑)(Bloom (FP) Crohn's 2008), inflammatory bowel (Segain 2000), Celiac (De Palma 2010) (BH) Healthy colon (Nava (ER) II (Larsen (CA) Colon cancer (Moore Moore, 1995), rheumatoid arthritis (Chen 2016) (EL) Cardiac drug (Haiser (Thota 2011), (DP) Regressive (Finegold (CH) None reported Synthetic arrayed chamber automated procedure (see Materials Methods). rich Methods) selected support growth all monospecies. serially transferred 24-h prevent lag phases being eliminated allow approach monitoring many cell generations. Further, serial also reflect recurrent perturbations diet colonic transit 1B). Multiplexed 12-h elucidate stages. relative computed sum read counts organism divided total reads condition Since construction aided absolute information (Bucci 2016; Widder 2016), biomass monitored 30 min (OD600). Cellular traits adhesion, size, (Stevenson addition, counting colony-forming units (CFU) biased dormant sub-populations, selection solid vs. liquid media, stage (Jansson Prosser, 1997; Volkmer Heinemann, Ou trained estimated thus automatically accounts any biases. infer interactions, (66 combinations) ratio values (PW1 dataset, Appendix Fig S1, Dataset EV1). Monospecies sequencing, broad range rates, carrying capacities (M S2). single-species dominance (Appendix S1). distribution PW1 provided insight variability presence second S3A). Absolute normalized maximum value evaluate baseline species. CH lowest coefficient variation (CV), indicating levels S3B). remaining bimodal (FP, DP, PC, BH, CA), long-tail (ER EL), and/or CV (ER, PC), altered further probe consortia, 15 2B, EV2) inoculated (95% A, 5% B, wherein percentages reversed) characterized our workflow (PW2 S4). classified following categories threshold 72 h: (i) dominance; (ii) both persisted above threshold; (iii) history dependence whereby mapped structures; (iv) did quantitatively satisfy thresholds cases 1–3. subset category weak potentially attributed biological replicates. qualitative 51 (t = 0) final h) PW2 reciprocal percentages, S5A). 50, 24, 12% dominance, coexistence, dependence, S5B). 2. Model training generalized function fits T3 represented points lines, respectively. subplot, x- y-axis, Stars datasets mean squared errors greater than 0.15. Error bars 1 s.d. least three Temporal 95% B values. Time Data lines T3, Inferred inter-species coefficients gLV T3. Gray green edges (αij < > coefficients. edge width node size magnitude (xe −μiαii−1), highlight significant less 1e-5 displayed. Construction growth, intra-species sensitivity. equations given by: where n, μ, αii, αij intra-species, coefficients, minimize overfitting data, regularized estimation implemented penalized Three sets evaluated capability: (T1) M; (T2) M, PW1; (T3) PW1, PW2. regularization (λ) scanned balance goodness fit sparsity S6). parameterized captured 2A B). accurately EL; CA; BO, CH; ER, BH; BH error between Thresholding yielded densely connected 77% pairs interaction. connectivity varied 75 79% ranging 1e-6 1e-3. Interaction 1e-3 expected change rate Of 56 21% positive, 2C). arise resource competition, by-products. secretion (BO, BV, BU, BT) net network, EL, positively stimulated S7A). unidirectional (−/0, 36%), bidirectional (−/−, 32%), (+/−, 26%) S7B). contribution full dictated coupled incoming Therefore, prediction about role requires simulation model. FP five determine abundance, examined 6-member FP, CH, DP. required alter twofold, dual moderately increased h S7C). enhanced conditions. Corroborating notion, Figs S3 Strong deciphered enhancement productivity compared null representing productivities integral S8). 38% twofold predictions models, consistent BU; BO; BT, BV; BO lower model, mutual inhibitory topologies BT; ER comparison (EL, ER) mutualism, augment productivity. Hierarchical clustering similar patterns S9A pattern relationships. distantly related display (e.g., DP PC CA) closely exhi

Язык: Английский

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Specific Bacteria and Metabolites Associated With Response to Fecal Microbiota Transplantation in Patients With Ulcerative Colitis

Gastroenterology, Год журнала: 2018, Номер 156(5), С. 1440 - 1454.e2

Опубликована: Дек. 6, 2018

Язык: Английский

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The Prevotella copri Complex Comprises Four Distinct Clades Underrepresented in Westernized Populations

Cell Host & Microbe, Год журнала: 2019, Номер 26(5), С. 666 - 679.e7

Опубликована: Окт. 10, 2019

Prevotella copri is a common human gut microbe that has been both positively and negatively associated with host health. In cross-continent meta-analysis exploiting >6,500 metagenomes, we obtained >1,000 genomes explored the genetic population structure of P. copri. encompasses four distinct clades (>10% inter-clade divergence) propose constitute complex, all were confirmed by isolate sequencing. These are nearly ubiquitous co-present in non-Westernized populations. Genomic analysis showed substantial functional diversity complex notable differences carbohydrate metabolism, suggesting multi-generational dietary modifications may be driving reduced prevalence Westernized Analysis ancient metagenomes highlighted patterns presence consistent modern populations clade delineation time pre-dating migratory waves out Africa. findings reveal exhibits high underrepresented Western-lifestyle

Язык: Английский

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The ancestral and industrialized gut microbiota and implications for human health

Nature Reviews Microbiology, Год журнала: 2019, Номер 17(6), С. 383 - 390

Опубликована: Май 15, 2019

Язык: Английский

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Distinct Genetic and Functional Traits of Human Intestinal Prevotella copri Strains Are Associated with Different Habitual Diets

Cell Host & Microbe, Год журнала: 2019, Номер 25(3), С. 444 - 453.e3

Опубликована: Фев. 23, 2019

Язык: Английский

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Gut microbiota in Parkinson's disease: Temporal stability and relations to disease progression

EBioMedicine, Год журнала: 2019, Номер 44, С. 691 - 707

Опубликована: Июнь 1, 2019

Several publications have described differences in cross-sectional comparisons of gut microbiota between patients with Parkinson's disease and control subjects, considerable variability the reported differentially abundant taxa. The temporal stability such alterations their relationship to progression not been previously studied a high-throughput sequencing based approach.We collected clinical data stool samples from 64 subjects twice, on average 2·25 years apart. Disease was evaluated changes Unified Rating Scale Levodopa Equivalent Dose, were characterized 16S rRNA gene amplicon sequencing.We compared controls, stable those faster progression. There significant microbial communities controls when corrected for confounders, but timepoints. Specific bacterial taxa that differed at both timepoints included several ones, as Roseburia, Prevotella Bifidobacterium. In comparisons, inconsistent across methods timepoints, there some support different distribution enterotypes decreased abundance faster-progressing patients.The detected persisted after 2 years. While we found evidence connection progression, longer follow-up period is required confirm these findings.

Язык: Английский

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