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  • Intestinal Microbiota During Life

    Patricia Conway

    The University of New South WalesSydney, Australia

  • OverviewAcquisition in the newbornFactors affecting the infant microbiotaDescribe the successive developmentFactors affecting the adult microbiota

  • Maternal and environmental eg hospital, siblings, pets AcquisitionInfant gut

  • Cabrera-Rubio et al , 2012Bacterial taxonomic composition of human breast milkBacterial families (left) and genera (right) pyrosequencing of the 16S rRNA.Col 1 month6 monthsVaginaNon-electiveElectiveColostrumBreast milkVaginaNon-electiveElective(NW= normal weight; OW=overweight)

  • Ward et al, 2013The percent of sequences assigned to each phyla according to MG-RAST (maximum e-value of1x10-5, minimum identity of 60%, and minimum alignment length of 45 bp)Best hit comparison of bacterial phyla in human milk,infants feces and mothers feces.

  • Utilization of human milk oligosaccharides by bifidobacteria B. longum subsp infantis: Infant strainOthers: Adult strains

    Sela & Mills, 2010

  • Bifidobacteria in breast milk: link with allergy/atopy of the mothers(Groenlund et al. Clinical & Exp Allergy 2007; 37: 1764 1772)

    Maternal breastmilk Bifi counts impacted the infants fecal Bifi levels (p = 0.013)

    Breastmilk bacteria: an important source of bacteria in the establishment of infantile intestinal microbiota Allergic mothers (atopic or non-atopic) have significantly fewer bifidobacteria in breastmilk

  • OverviewAcquisition in the newbornFactors affecting the infant microbiotaDescribe the successive developmentFactors affecting the adult microbiota

  • Microbiota at various sites for mother and infant

  • Impact of gestation time

  • Figure 3. Changes in proportion of bacterial phyla.Mai V, Young CM, Ukhanova M, Wang X, et al. (2011) Fecal Microbiota in Premature Infants Prior to Necrotizing Enterocolitis. PLoS ONE 6(6): e20647. doi:10.1371/journal.pone.0020647http://www.plosone.org/article/info:doi/10.1371/journal.pone.0020647Fecal microbiota in preterms prior to NEC

  • Microbiota of infants in Europe & Africa

  • Impact of antibiotics & diet on microbiota

  • Colicky Infants

  • Window of sensitivity around 4-6 months of ageGut microbiota pivotal role in maturation of immune system

  • Infants of 6 to 11 months old are more prone to diarrhea than older children(Kosek, WHO Bulletin, 2003)

  • Microbiota and the emerging pandemic of NCDs(Non-Communicable Diseases)NCDs: Allergy, obesity, diabetes, cardiovascular disease, mental health and auto-immune diseases Life style choicesHealthNCDs

  • OverviewAcquisition in the newbornFactors affecting the infant microbiotaDescribe the successive developmentFactors affecting the adult microbiota

  • The function of our microbiota: who is out there and what do they do?Ottman et al (2012) Front. Cell. Infect. Microbiol(doi: 10.3389/fcimb.2012.00104)

  • Mariat et al, 2009Change in major bacteria groups in the elderly - Can induce an inflammatory responseMagrone and Jirillo, 2013

  • OverviewAcquisition in the newbornFactors affecting the infant microbiotaDescribe the successive developmentFactors affecting the adult microbiota

  • Factors Impacting on Adult Gut MicrobiotaLife style choicesMedicationsDietStressors AgeInstitution care or home livingDental healthInfectionHygieneSanitizationUrban/rural

  • Diversity differences linked to age and cultureLuzupone et al 2012USA & Europe

  • Phylum/order-like phylogroups to the microbiota of varying agesBiagi E, Nylund L, Candela M, Ostan R, et al. (2010) Through Ageing, and Beyond: Gut Microbiota and Inflammatory Status in Seniors and Centenarians. PLoS ONE 5(5): e10667. doi:10.1371/journal.pone.0010667C = centenariansE = elderlyY = young adults

  • Microbiota composition and plasma levels of pro-inflammatory cytokines.Biagi E, Nylund L, Candela M, Ostan R, et al. (2010) Through Ageing, and Beyond: Gut Microbiota and Inflammatory Status in Seniors and Centenarians. PLoS ONE 5(5): e10667. doi:10.1371/journal.pone.0010667http://www.plosone.org/article/info:doi/10.1371/journal.pone.0010667Green = centenarians (C)Blue = elderly/senior (S)Yellow = young (Y)

  • MJ Claesson et al. Nature (2012), 1-7 Microbiota analysis separates elderly subjects based upon where they live in the community.Green = community; Yellow = day hospital; orange = rehabilitationred = long stay care; purple = young healthy controls.

  • MJ Claesson et al. Nature (2012) (doi:10.1038/nature11319)Transition in microbiota composition across residence location is mirrored by changes in health indices.Clustered according to residence locationComposition correlates with:- frailty- nutrition- markers of inflammation- metabolism

  • SUMMARY

  • Thank You

    *16S rRNA gene surveys reveal a clear separation of two children populations investigated. (AandB) Pie charts of median values of bacterial genera present in fecal samples of BF and EU children (>3%) found by RDP classifier v. 2.1. Rings represent corresponding phylum (Bacteroidetes in green and Firmicutes in red) for each of the most frequently represented genera. (C) Dendrogram obtained with complete linkage hierarchical clustering of the samples from BF and EU populations based on their genera. The subcluster located in the middle of the tree contains samples taken from the three youngest (12 y old) children of the BF group (16BF, 3BF, and 4BF) and two 1-y-old children of the EU group (2EU and 3EU). (D) Relative abundances (percentage of sequences) of the four most abundant bacterial phyla in each individual among the BF and EU children. Blue area in middle shows abundance of Actinobacteria, mainly represented byBifidobacteriumgenus, in the five youngest EU and BF children. (E) Relative abundance (percentage of sequences) of Gram-negative and Gram-positive bacteria in each individual. Different distributions of Gram-negative and Gram-positive in the BF and EU populations reflect differences in the two most represented phyla, Bacteroidetes and Firmicutes.*Human microbial diversity and enterotypes. Enterotypes31 weredetermined when evaluating only adults from the United States and Europe(circled in white). By including children from the United States and childrenand adults from developing countries, the picture of human-associatedmicrobiota diversity greatly expands. The relationship between the microbiotaof 531 healthy children and adults from Malawi, Amazonas state of Venezuela(Amerindians) and the United States was evaluated using sequences fromthe 16S rRNA gene in faecal samples and a principle coordinate analysisof unweighted UniFrac distances (adapted with permission from ref. 4). a,Infants differentiate strongly from adults, and b, adults from the United Stateshave a distinct composition from those of Malawi and Venezuela, indicatingthe diversity differences are mainly owing to age and culture.*Correlation between microbiota composition and plasma levels of pro-inflammatory cytokines. In the RDA blood cytokinelevels (red arrows) and age groups (C, S, and Y, red triangles) are used as linear and nominal environmental variables, respectively. Samples belongingto C, S and Y groups are indicated by green circles, blue squares and yellow diamonds, respectively. Responding bacterial subgroups that explainedmore than 20% of the variability of the samples are indicated by black arrows. First and second ordination axes are plotted, showing 5.8% and 3.1% ofthe variability in the dataset, respectively. Red arrows which are not labelled corresponds to (clockwise, starting from the left) TNF-a, IFN-c, IL-2, IL-1a,IL-12p70, and IL-1b. Log transformed data were used for this analysis. Bottom-left, P value obtained by MCPP is reported. Top-left, average bloodlevels of IL-6 and IL-8 in groups C, S and Y are reported.*Microbiota analysis separates elderly subjects based upon wherethey live in the community. a, Unweighted and b, weighted UniFrac PCoA offaecal microbiota from 191 subjects. Subject colour coding: green, community;yellow, day hospital; orange, rehabilitation; red, long-stay; and purple, younghealthy control subjects. c, Hierarchical Ward-linkage clustering based on theSpearman correlation coefficients of the proportion of OTUs, filtered for OTUsubject prevalence of at least 20%. Subjects colour coding as in a. Labelledclusters in top of panel c (basis for the eight groups in Fig. 4) are highlighted byblack squares. OTUs are clustered by the vertical tree, colour-coded by familyassignments. Bacteroidetes phylum, blue gradient; Firmicutes, red;Proteobacteria, green; and Actinobacteria, yellow. Only 774 OTUs confidentlyclassified to family level are visualized. The bottom panel shows relativeabundance of family-classified microbiota.*Transition in microbiota composition across residence location ismirrored by changes in health indices. The PCoA plots show 8 groups ofsubjects defined by unweighted UniFrac microbiota analysis of communitysubjects (left), the whole cohort (centre), and long-stay subjects (right). Themain circle shows the Wiggum plots corresponding to the 8 groups fromwhole-cohort analysis, in which disc sizes indicate genus over-abundancerelative to background. The pie charts show residence location proportions(colour coded as in Fig. 1c) and number of subjects per subject group. Curvedarrows indicate transition from health (green) to frailty (red). FIM, functionalindependence measure; MNA, mini nutritional assessment; GDT, geriatricdepression test; CC, calf circumference; CRP, C-reactive protein; IL,interleukin; BP, blood pressure; MMSE, mini-mental state examination.**