Table of content Presentations Speaker
Title
Aagaard K.
Almeida M.
A comprehensive metagenomic catalogue of microbiota across body sites in Primates: A high fat maternal diet alters the offspring microbiome to 1 year of age From "meta-genomic species" to high quality draft genomes
10
Arumugam M.
Towards petabase metagenomics : challenges and roadblocks ahead
11
Blaser M.
Effects of early life antibiotics on murine developmental phenotypes and immunity Complexity and individuality of human gut microbiomes
12
14
Clement K.
Identification of Crohn’s Signatures in the Human Gut Microbiota by Metaomics Gut metagenome: clinical investigation studies
Collins S.M.
The Influence of the intestinal microbiota on the gut-brain axis
16
Cotter P.
Modulation of the gut microbiota; antibiotics vs. bacteriocins
17
Derrien M.
18
Ehrlich S.D.
Impact of consumption of a fermented milk product on gut microbiota stability and functionality in ulcerative patients From Associations to Causality: Effect of Treatments Targeting the Human Intestinal Microbiome Functional metagenomics of the crosstalk between commensal gut bacteria and human cells Lessons from the MetaHIT project
Finlay B.B.
The role of microbiota in enteric and allergic diseases
22
Gevers D.
Baseline for a healthy human microbiome
23
Goedert
Fecal Microbial Determinants of Fecal and Systemic Estrogens
24
Guarner F.
Distortion of the gut microbial ecosystem in patients with ulcerative colitis
25
Hattori M.
Metagenomics of Japanese gut microbiomes
26
Hoffmann C.
Long term dietary patterns shape gut microbial enterotypes
27
Huttenhower C.
28
Junhua L.
Reducing microbial unemployment: functional roles for the microbiome in health and disease Improvement of microbial gene catalog construction
Knight R.
Sources of variation in the human microbiome
30
Knights D.
Human--‐Associated Microbial Signatures: Examining Their Predictive Value
31
Leclerc M.
32
Nelson K.
Riboflavin production by a metagenomic clone from the human ileum mucosa: a new role for Faecalibacterium prausnitzii in vivo? The intestinal dysbiosis and its contribution to NAFLD in human and the high-fat induced rats Reference genomes for the study of the human microbiome
Nielsen B.
MetaGenomic-Species: facilitating statistical and biological interpretation
35
Nielsen J.
Prospects for Systems Biology and Modeling of the Gut Microbiome
36
O’Toole P.
Diet-health-microbiota interactions in older persons
37
Pedersen O.
38
Pop M.
Deep metagenomic sequencing demonstrates marked differences in the gut microbiome between lean and obese people: evidence from the MetaHit obesity study Uncovering the dark matter of the human microbiota through high throughput single cell genomics and targeted pangenomics Can we and should we assemble metagenomes ?
Ravel J.
Transcriptional dynamics of the vaginal microbiome
41
Bork, P. Cantarel B.
De Vos W. Dore J.
Lanjuan L.
Podar M.
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13
15
19 20 21
29
33 34
39 40
Speaker
Title
Relman D.
Stability and Resilience in the Human Microbiome
42
Slashinski M.
Ethical, Legal, and Social Dimensions of Human Microbiome Research
43
Sobhani I.
Putative role of gene mutation and environment in colon cancer inflammation in host
44
Versalovic J.
45
White O.
Network Analysis Reveals Altered Community Structure in the Fecal Microbiota of Children with Irritable Bowel Syndrome A Metagenome-Wide Association Study of gut microbiota identifies markers associated with Type 2 Diabetes The Human Microbiome Project Analysis Infrastructure
Wylie K.
Novel Bacterial Taxa in the Human and Vervet Microbiomes
48
Zhao L.
＂Microbiome-wide association studies，MiWAS＂ for dissecting the role of gut microbiota in metabolic syndrome, from animal models to human trials
49
Wang J.
Page
46 47
Posters Poster Author N. 137
Title
A 16s‐based metagenomic approach to characterization of the vaginal microbiome signature in pregnancy Abdollahi-Roodsaz Critical role of mouse microbiota and efficacy of dietary non-digestible S. oligosaccharide treatment in Th17-dependent autoimmune destructive arthritis
50
164
Abnet C.C.
Upper digestive tract microbiome diversity is associated with total mortality in a prospective cohort study in China
52
128
Alban, M.
Life on human surfaces: skin metagenomics.
53
126
Alekseyenko A.V.
Association of cutaneous microbiota with psoriasis
54
57
Alexeev D.G.
Human gut microbiota analyzed by mass-spectrometry and sequencing
55
92
Alicki E.
The impact of IgA on the intestinal microbiome
56
136
Aliferis C.F.
Microbiomic Signatures of Psoriasis: Feasibility and Methodology Comparison
57
5
Azad M.B.
Exclusive breastfeeding protects against Clostridium difficile colonization by promoting lower relative abundance of Lachnospiraceae in gut microbiota.
58
68
Ballarini A.
Species-level profiling of human microbiomes with the BactoChip microarray
59
108
Batto J.M.
Optimizations to compute large correlation matrix onto GPU system of hybrid HPC clusters
60
15
Beighton D.
In vivo expression of glycan utilization genes by Streptococcus oralis and Streptococcus mitis in the oral cavity.
61
28
Belzer C.
Function and importance of Akkermansia spp. in the intestinal tract
62
162
Biesbroek, G.
63
160
Biesbroek, G.
161
Biesbroek, G.
82
Brown J.R.
The nasopharyngeal microbiota in relation to 7-valent Pneumococcal Conjugate Vaccination: a randomized controlled trial in healthy children in The Netherlands Effect of Feeding type on the Composition and Dynamics of Nasopharyngeal Microbiota in Infants Viral and Bacterial Interactions in the Upper Respiratory tract of Healthy Children: a metagenomic approach Antibacterial Drug Modulation of the Gut Microbiome in Obesity and Diabetes Animal Models
54
Budding A.E.
Evaluation of rectal swabs for the analysis of human intestinal microbiota
67
53
Budding A.E.
Automated high througput analysis of the intestinal microbiota by IS-pro
68
81
Aagaard K.
Page
51
64 65 66
Poster Author N.
Title
Page
86
Bülow E.
Functional metagenomic analysis reveals selection for antibiotic resistance in the gut microbiota during Intensive Care hospitalization
69
120
Bylova N.
Gut microbiota in chronic heart failure (CHF)
70
39
Campbell A.G.
Single cell genomics of uncultured oral Chloroflexi, Deltaproteobacteria and Synergistes
71
47
Campbell J.H.
Single-cell genomic characterization of human oral representatives of the incultured SR1 and TM7 bacterial phyla.
72
144
Charlson E.S.
Biogeography of microbial populations in the respiratory tract of healthy and HIV-infected subjects
73
85
Chunlei Chen
Antioxidant-Protective Effects of Lactitol against Endotoxemia in Patients with Chronic Viral Hepatitis
74
70
Chen Yu
Association of oral health, oral bacterial infection, and gastric precancerous lesions
75
150
Chiang H-I
Hybrid assembly of metagenomic and single-cell genome sequencing data
76
Claesson M.J.
Resolving Additional Microbiota Subtypes in Intestinal Microbiota of Older Subjects
77
110
Collison M.
A data integration platform for the microbiota
78
33
Couvigny B.
The commensal bacterium Streptococcus salivarius inhibits PPARγ activity and its target genes in human intestinal epithelial cells.
79
1
Cox L.M.
Early life microbiota alters adult metabolism and body composition
80
19
Danilenko V.N.
81
12
Davenport E.
The Toxin-Antitoxin System Gene Polymorphism As A Marker for Species and Strain Identification of the Probiotic Component of Human Microbiome Examining the genetic basis of interindividual variation in the human fecal microbiome
72
de Leeuw M.
16S metagenomics profiling
83
59
Di Liberto G.
Functional analysis of the predicted surface proteome of Gram+ bacteria from the human GI tract.
84
29
Do T.
Evidence of ethanolamine catabolism by Fusobacteria.
85
140
Dols J.A.M.
86
148
Durbán A.
Bacteria associated with bacterial vaginosis in HIV-positive Tanzanian women: Correlation analysis between results from 16S-rDNA-based microarrays, microscopy and Whiff tests Follow-up of faecal microbiota in irritable bowel syndrome patients.
147
Durbán A.
Dynamics of faecal bacterial communities based on daily follow-up
88
151
Dutilh B.E.
Towards the human colorectal cancer microbiome
89
73
Earl A.
The Most Wanted Bacteria from the Human Microbiome
90
87
Eloe-Fadrosh E.A.
Effects of oral immunization with the Ty21a typhoid vaccine on the gut microbiota and local and Systemic immune responses
91
96
Faust K.
Prediction of relationships between microbial taxa in the human body
92
48
Feehery G.R.
Novel purification reagents for the study of the human microbiome
93
130
Fettweis J.M.
The vaginal microbiome: disease, genetics and the environment
94
42
Flores R.
Effect of Delayed Freezing on Microbial Composition in Human Feces: Lessons for Epidemiological Studies
95
127
Fouad A.F.
Transformation of oral microbiome from normal oral cavity to acute endodontic infections
96
Francino, M. P.
97
99
4
2 152
Fricke W.F.
Meconium microbiota types: relation to maternal and childbirth determinants and to health outcomes in early childhood The fungal and bacterial microbiome of the stomach
129
Gajer P.M.
Association between cigarette smoking and the vaginal microbiota
82
87
98
Poster Author N.
Title
Page
141
Ganu R.
Linking barkers hypothesis on the developmental origins of adult disease with the hygiene hypothesis: maternal methyl-donor supplementation (MDS) significantly alters the fetal liver microbiome
100
142
Ganu R.
Remote history of maternal infection or asymptomatic vaginosis alters the human placental microbiome
101
125
Garcia-Garcerà M.
Staphylococcus prevails in the skin microbiota of long-term immunodeficient mice.
102
Gon le A.
Assessing temporal changes in microbial communities.
103
138
Gorkiewicz G.
Dysbiosis and altered mucosal immune response in chronic inflammatory upper gastrointestinal (GI) diseases.
104
20
Guédon E.
Relationship between self-aggregation property of the human commensal bacterium Streptococcus salivarius and its ability to interact with intestinal epithelial cells
105
30
Haiser H.J.
Characterizing the inactivation of the cardiac drug, digoxin, by a member of the human gut microbiota
106
56
Han C.S.
Artificial Polyploidy Improves Genome Coverage from Single Cell
107
55
Hao Qin
A mouse fecal microbial gene catalogue established by Illumina-based sequencing
108
100
Hendriksen W.T.
Modeling pathways of nasopharyngeal microbiota of young children based on 16S rRNA sequence data: an exploratory study
109
49
Hettich R.
A hybrid metagenomic sequencing and assembly approach increases proteome identification coverage in the human gut microbiome
110
114
Hildebrand F.
Combining a gut-specific annotation platform with a dedicated datamining pipeline towards understanding obese and IBD microbiota
111
89
Hooda S.
Fecal microbiota of healthy adult men is affected by novel dietary fibers and correlated with fecal metabolites
112
101
Hunter C.
EBI Metagenomics: Studying the Functions of Metagenomes.
113
99
Huot Creasy, H.
The Data Analysis and Coordination Center for the Human Microbiome Project
114
51
Isaksen M.L.
GA-map™ - a rapid, comprehensive gut microbiota analysis
115
65
Jalanka-Tuovinen J.
Intestinal microbiota in healthy adults: dimensions of the common core and relation to intestinal symptoms
116
90
Jeffery I.B.
Microbial diversity is highly correlated with the Healthy Food Diversity Index
117
157
Joossens M.
Functional Repercussions of Subclinical Intestinal Dysbiosis In Unaffected Relatives Of Crohn’s Disease Patients
118
21
Kaci G.
Anti-inflammatory properties of commensal Streptococcus salivarius on human intestinal epithelial cells and in murine TNBS-induced colitis model
119
143
Karlsson F.
Atherosclerosis is associated with an altered gut metagenome
120
43
Keijser B.J.F.
A public-private partnership that aims to establish a novel, multivariate view of oral health
121
145
Kistler J.O
Bacterial Composition of Dental Plaque during the Transition from Health to Experimentally Induced Gingivitis
122
135
Ko, G.P.
Association studies on vaginal microbiota with human papillomavirus infection and menopause in a Korean twin cohort
91
Kolmeder C.
Effects of a probiotic intervention on the human intestinal metaproteome
18
Kong, L.C.
Association between gut microbiota and adipose tissue gene expression during bariatric surgery induced weight loss in morbid obesity
6
123 124 125
Poster Author N.
Title
Page
7
Konya T.
Is house dust a reservoir for gut bacteria?
126
75
Kotowska D.
Changes in gut microbiota in resveratol treated and exercised aged mice.
127
22
Kushugulova A.R.
Study of the properties of bacteria of the genus Lactobacillus, representatives of intestinal microbiota
128
103
La Rosa P.S.
Modeling and Clustering Taxonomic Trees from Human Microbiome Data using Statistical Object-Oriented Data Analysis
129
67
Lahti L.
Global characterization of the human intestinal microbiota by integrative metaanalysis
130
24
Langella P.
Analysis of anti-inflammatory effects of FaecalibacteriumI prausnitzii using gnotobiotic mice
131
102
Langille M.G.I.
Inferring microbial community function from taxonomic composition
132
23
Layec S.
Impact of surface‐exposed proteins on the commensal life in Streptococccus salivarius.
133
50
Lewis C.M.
Characterizing Extinct Gut Microbiomes
134
32
Li Huiying
Propionibacterium acnes strain populations in the skin microbiome associated with acne
135
34
Luang-In V.
Influence of human gut microbiota on the metabolic fate of glucosinolates
136
8
Luna R.A.
Temporal characterization of the gut microbiome in a cohort of hospitalized preterm infants
137
13
Ma Jun
Initial association study of human microbiome profile with its host mitochondria genome variants
138
38
Mackie, R.
Transcriptional analysis of wheat arabinoxylan hydrolysis and utilization by Bacteroides ovatus and Bacteroides intestinalis
139
153
Mai, V.
Fecal Microbiota Distortions Appear Associated with Late Onset Sepsis in Preterm Infants
140
131
Mändar, R.
Effect of sexual intercourse on vaginal microbiome of infertile couples’ women
141
167
Manichanh, C.
A robust microbiota: a key protagonist against functional intestinal disorders?
142
166
Manichanh, C.
Storage conditions of intestinal microbiota matter in functional metagenomics
143
63
Maukonen J.
The currently used commercial DNA extraction methods give different results of Clostridial and Actinobacterial populations derived from human fecal samples
144
58
Maurice, C.
An active subset of the human gut microbiome responsive to xenobiotics
145
105
Miller, C.S.
EMIRGE: Sensitive, quantitative microbial community characterization via deep sequencing and assembly of full-length 16S amplicons.
146
154
Minot, S.
The human gut virome: Inter-individual diversity, genomic hypervariation, and dynamic response to diet
147
83
Morrison M.
148
84
Morrison M.
60
Murugkar P.P.
Weight loss associated dietary intervention affects the human gut microbiota in obese but otherwise healthy Australian males and changes in the growth of Faecalibacterium praunitzii in response to changes in nutrient profiles A “metaparental mating” approach for the recovery of new transconjugant strains of human gut bacteria Mechanisms of Uncultivability in the Oral Microbiome
139
Nakayama J.
Asian Microbiome Project: A pilot study on the basal microbiota profile of healthy Asian youngsters
151
113
Nookaew J.
Enterotype analysis of 317 gut metagenomes
152
149 150
Poster Author N.
Title
Page
165
Obregón-Tito A.J.
Metagenomics and social inclusion in Peru
153
168
Ogilvie L.A.
Comparative (meta)genomic analysis and ecological profiling of human gutspecific bacteriophage ɸB124-14.
154
169
Patsantara G.
Parasitic helminth Enterobius vermicularis as a commensal microorganism
155
155
Pérez-Brocal V.
An approach to the characteri ation of the human virome in Crohn’s disease
156
106
Pesole G.
SARMA: a web resource for species assignment of high--‐throughput sequencing reads from Metagenomics Analysis
157
146
Philllips G.J.
Dysbiosis characterised by reduced abundance of Roseburia is associated with -/increased severity of colitis in Il-10 mice
158
31
Pieper D.H.
The anterior nare microbial community over space and time
156
Pinto J.
Sinonasal Microbiota Vary with Disease Subtype: Implications for Mucosal Inflammatory Disorders of the Upper Airway
159 160
115
Plichta D.R.
Functional analysis of novel genetic structures indentified through metagenomics of human gut.
161
94
Popenko A.S.
MALINA - a Web-service for human gut microbiota whole-genome metagenomic reads analysis
162
9
Putignani L.
Succession of early microbial consortia in the developing infant intestinal microbiota unveiled by meta-omics approaches
163
158
Qin Nan
Analysis of gut microbiome in patients with liver cirrhosis
164
111
Raes J.
165
159
Redel H.
Microbiome variation in health and disease: how to get more out of your metagenome Quantitation of cutaneous microbiota in diabetic and non-diabetic men
25
Renault P.
Prevalence of Streptococci in the intestinal flora
167
44
Rho M.
CRISPRs: Evolving immune systems in human microbiomes
168
107
Riehle K.
The Genboree Microbiome Toolset and Microbiome Analysis
169
16
Roeselers G.
A Top-down microbial systems ecology view of the impact of prebiotic oligosacharides on Bifidobacteria in a Human gut microcosm
170
76
Roger L.
Monitoring the Effects of Black Tea Polyphenols on the Human Intestinal Microbial Ecosystem in vitro
171
116
Said H.S.
Comparative Analysis of Salivary Microbiota of IBD Patients and Healthy Individuals using Barcoded Pyrosequencing
172
66
Salojärvi J.
Meta-analysis of the Human Gut Microbiota - Focus on Enterotypes
173
122
Sanz Y.
Genetic risk of developing coeliac disease and milk-feeding type influence the intestinal colonization pattern in infants. The PROFICEL study
174
117
Saulnier D.M.
Volatile metabolite production and microbiome composition in halitosis
175
41
Scheffer-Wong A.
Massively Parallel Synthesis of Oligonucleotides Enables Fluorescence In Situ Hybridization (FISH) to Microbial Genomes
176
77
Schioppa T.
Probiotic and postbiotic activity in health and disease: comparison on a novel polarized ex-vivo organ culture model.
177
95
Schmieder R.
Tools for Detecting Antibiotic Resistance in the Human Microbiome
178
74
Seekatz A.
The Effect of an Oral Live‐attenuated Shigella Vaccine and Wild type Shigella Infection on the Intestinal Microbiota of Cynomolgus Monkeys
179
118
Segal L.N.
Evaluation of the upper airway and lung microbiome in emphysema
180
104
Segata N.
Efficient metagenomic community profiling enables species-level characterization of over 250 shotgun sequenced gut microbiomes
181
166
Poster Author N.
Title
Page
64
Shah P.
A biomolecular isolation framework for molecular Eco-Systems Biology of the human microbiome
182
97
Sharma V.K.
Comparative Analysis of MetaBin with Other Homology-based Methods for Taxonomic Assignments of Metagenomic Sequences
183
109
Sharpton T.J.
Quantifying Human Microbiome Functional Variation using Operational Protein Families
184
93
Shoaie S.
Modeling of human gut microbiome
185
40
Sim K.
Missing bifidobacteria: systematic undercounting in neonatal gastrointestinal microbiota resolved with novel, universal, barcoded 454 primers.
186
98
Smith A.M.
Development of a hierarchical taxonomy assignment pipeline for fungal microbiomics
187
78
Sonne S.B.
Modulation of the gut microbiota by diets and the anti-inflammatory drug indomethacin in obesity prone and obesity resistant mice
188
69
Spencer M.D.
Robust data management and analysis strategies overcome sequencing platform idiosyncrasies
189
35
Spinler J.K.
Pangenomic analysis of Lactobacillus reuteri highlights the evolution of a human-specific ecotype
190
36
Srivastava T.
Complete genome sequences of rat and mouse strains of unculturable Segmented Filamentous Bacteria, a potent inducer of Th17 cell differentiation.
191
133
Stahringer S.S.
A longitudinal survey of the oral microbiota in adolescent twins
192
52
Stamboliyska R.
Identification of prokaryotic transposable elements from metagenomic marine data
193
37
Thiele I.
Systems biology approach to the human–Bacteroides thetaiotaomicron symbiosis
194
61
Thompson H.
An in-vitro model system for the cultivation of previously uncultured human oral bacteria
195
45
Tims S.
Development of a carbohydrate binding protein detection assay
196
26
Tomida S.
The pan-genome and strain diversity of Propionibacterium acnes in the human skin microbiome
197
149
Tong M.
Defining a mosaic of functional microbial communities at the human mucosal surface, and their association with IBD
198
112
Treangen T.
163
Tyakht A.V.
Examining composition of Russian human gut microbiota by assessing relative abundance of functional and taxonomical units
200
11
Tyler A.D.
Interaction of IBD-associated genetic polymorphisms and the microbiome of the pelvic pouch
201
17
Ubeda C.
Commensal anaerobic bacteria mediate Vancomycin-resistant Enterococcus clearance from the intestine.
202
3
Valles Y.
Acquisition and development of the gut microbiota
203
123
Van der Pol B.
Impact of Chlamydial Infection on Male Urethra Microbiota
204
119
Vincent C.
The intestinal microbiota as a predictor for nosocomial Clostridium difficile infection
205
14
Wacklin P.
Secretor genotype (FUT2 gene) is associated with composition of bacteria in the human intestine
206
metAMOS: A modular and open source metagenomic assembly pipeline
199
Poster Author N.
Title
Page
10
Wang Duochun
Genome sequencing reveals unique mutations in characteristic metabolic pathways and the transfer of virulence genes between V. mimicus and V. cholerae
207
27
Wang Xinhui
Patterns on the composition of nasopharyngeal microbiota
208
79
Ward D.V.
Impact of antibiotic administration on the establishment and development of infant gut flora
209
121
Winek K.
The impact of focal cerebral ischaemia on the composition of murine intestinal microbiota
210
62
Witt K.
Identifying mechanisms of bacterial unculturability in the human gut microbiome
211
170
Wylie K.
The Human Virome in Healthy Adults
212
88
Xiang C.
Vaginal microbiota restoration for bacterial vaginosis treated with metronidazole and probiotic Lactobacillus intravaginally
213
80
Yamanishi S.
Down-regulation of mucosal immune system in mice exposed to early life antibiotic treatments
214
71
Yang Liying
Reproducibility and accuracy of amplicon-based 16S rRNA gene surveys
215
132
Youmans B.
Alterations in the human gut microbiome during and after norovirus-associated travelers’ diarrhea
216
46
Yow M.A.
Pathogen discovery in prostate cancer: a massively parallel sequencing approach
217
124
Zaura E.
The relation between oral Candida load and bacterial microbiome profiles in Dutch elderly
218
134
Zhou Xia
Characterization of Microbiota in External Urogenital and Perianal Areas of Women
219
A COMPREHENSIVE METAGENOMIC CATALOGUE OF MICROBIOTA ACROSS BODY SITES IN PRIMATES: A HIGH FAT MATERNAL DIET ALTERS THE OFFSPRING MICROBIOME TO 1 YEAR OF AGE Kjersti Aagaard1, Radhika Ganu1, Antonio Frias2, Jun Ma1, Diana Takahashi3, Joseph Petrosino4, Kevin Grove5, James Versalovic6 1 Baylor College of Medicine, Obstetrics&Gynecology, Division of Maternal‐Fetal Medicine, Houston, TX, 2Oregon Health & Science University, Maternal Fetal Medicine, Portland, OR, 3Oregon Health & Science University, Oregon National Primate Research Center, Beaverton, OR, 4Baylor College of Medicine, Molecular Virology and Microbiology, Houston, TX, 5Oregon Health Sciences University, Oregon National Primate Research Center, Beaverton, OR, 6Baylor College of Medicine and Texas Children's Hospital, Pathology & Immunology, Houston, TX
[email protected] Microbiota are present from birth with up to 10‐fold the number of organisms (the "microbiome") and a collective genome (the “metagenome”) which exceeds ours by >100‐fold. An altered gut microbiome has been described in association with obesity and other disease states. However, how and when these altered microbiota communities take up residence are under explored. We reasoned that our well‐characterized primate model of maternal obesity would be an ideal means to decipher the relative contribution of maternal diet, obesity, and microbiota on the developmental microbiome. Age and weight‐matched dams were placed on control (13%) or HF (35%) diets. Over the study interval, distinct maternal cohorts emerged: obese HF diet sensitive [HFS], obesity‐ resistant [HFR], and lean [CTR]. 161 comprehensive body site samples (placenta, oral, GI, fecal, GU) from these dams and their offspring (fetal and 1yr) were deep sequenced (16S V5V3 rRNA gDNA; 454FLXTitanium). Data were QC filtered and exhaustively analyzed (OTU, genera; Canberra) using our custom supervised learning and QIIME pipelines. Extensive computational analysis was performed on 596 megabytes of generated metagenomic data (>1.8 million filtered reads of 494nt). We observed significant clustering of maternal and offspring (fetal and 1yr) OTU predominately by body site (>3285 OTU genera). Of noted interest, at 1yr of age the core gut microbiome is defined by a HF maternal diet and irrespective of obesity nor postwean diet . Using limited discriminate sets, we were able to classify offspring microbiome profiles by maternal diet (RandomForrest, 91.5% success). The maternal gut microbiome does not cluster by HFD. Employing state of the art metagenomics, we demonstrate that 16S‐based microbiome communities are conserved across primate species. Moreover, maternal diet (not obesity nor postnatal diet) establishes a perturbed microbiome in the offspring. These data suggest that the maternal diet profoundly influences the offspring microbiome and may thus serve to arbitrate later in life obesity.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
From "meta‐genomic species" to high quality draft genomes. Almeida Mathieu1, Rasmussen Simon2, Sunagawa Shinichi3, Gautier Laurent2 Moumen Bouziane1, Pelletier Eric4, Pons Nicolas1, Batto Jean‐Michel1, Le Chatelier Emmanuelle1, Brunak SØren2, Renault Pierre1, Bork Peer3, Nielsen H. BjØrn2, Ehrlich S. Dusko1. MICALIS Institute, INRA Jouy‐en‐Josas, France ; 2 Center for Biological Sequence Analysis, DTU, Denmark; 3 EMBL, Heidelberg, Germany; 4 Genoscope, CEA, France.
[email protected],
[email protected] 1
The MetaHit human intestinal microbiome gene catalog (Qin et al. 2010) was extended to 3.9M genes throughout 396 stool samples (to be released shortly). However, less than 20% of the genes can be assigned taxonomy based on sequence similarity to known reference genomes (at 85% identity over 100bp). Alternatively, we reasoned that genes from the same DNA molecule (chromosome, etc.) should have very similar abundance profiles throughout the sample series. Using this co-abundance principle, 700 large Meta-Genomic Species (MGS), defined as clusters of tightly co-varying genes in metagenomic samples, were obtained. The majority of these MGS have no closely related reference genomes. By reassembling subsets of Illumina reads that match the co-varying MGS genes, and thereby reducing the sequence ambiguity, more than 40 MGS reached the HMP criteria for high quality draft genomes. In addition, more than 200 MGS matched 4 out of 6 criteria. This demonstrates, that meta-genomic sequencing of a series of human microbiome samples can yield high quality draft genomes without cultivation or single cell sequencing, and thus can contribute significantly with in nature captured reference genomes to the HMP set.
Towards petabase metagenomics : challenges and roadblocks ahead Manimozhiyan Arumugam EMBL, Meyerhofstrasse 1, 69117 Heidelberg
[email protected] Introduction of next‐generation sequencing into metagenomics has revolutionized the field while bringing an array of new challenges. The sheer amount of metagenomic data associated with large‐ scale microbiome studies such as MetaHIT and the Human Microbiome Project requires us to review metagenomic analysis tools. We identify several challenges while analyzing hundreds of samples using a metagenomic analysis pipeline optimized for next‐generation shotgun metagenomic sequences. We revisit the stratification of humans into enterotypes based on the gut microbial community composition and emphasize that consistent treatment and accounting for vital metadata are essential for proper interpretation of the results.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
Effects of early life antibiotics on murine developmental phenotypes and immunity Martin J. Blaser, Laurie Cox, Shingo Yamanishi, Yael Nobel, Alexander V. Alekseyenko, Ilseung Cho, Douglas Mahana, Isabel Teitler, Kathie Mihindukulasuriya, George Weinstock, Erica Sodergren Antibiotic usage in human children for the treatment of early life infections is intensive, and is a relatively new (2.5 million reads (averaging 6,837 sequences/sample of 493 nt in length) were generated for computational analyses. A unique vaginal microbiome signature encompassing several specific OTUs and higher‐ level clades was observed and confirmed using a combination of phylogenetic, non‐phylogenetic, supervised, and unsupervised approaches. Both overall diversity and genus‐level richness were reduced in pregnancy. This intergroup comparison using rigorous standardized sampling protocols and analytical methodologies provides robust initial evidence that the vaginal microbial 16S rRNA gene catalogue uniquely differs in pregnancy, with variance of taxa across vaginal subsite and gestational age.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
Critical role of mouse microbiota and efficacy of dietary non‐digestible oligosaccharide treatment in Th17‐dependent autoimmune destructive arthritis Shahla Abdollahi‐Roodsaz1, Anita Hartog2, Sander de Kivit3, Fons van de Loo1, Birgitte Walgreen1, Liduine van den Bersselaar1, Monique Helsen1, Harm Wopereis2, Raish Oozeer2, Paul Vos2, Johan Garssen2,3, Linette Willemsen3 and Wim van den Berg1 1
Rheumatology Research & Advanced Therapeutics, Department of Rheumatology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands; 2Danone Reseacrh, Wageningen, The Netherlands; 3 Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands. S. Abdollahi‐Roodsaz, PO Box 9101, 6500HB, Nijmegen, The Netherlands S.Abdollahi‐
[email protected]
The aim of the present study was to investigate the involvement of intestinal microbiota in the development of T cell‐dependent autoimmune arthritis and to assess the feasibility of microbiota modulation as a therapeutic approach. Using interleukin‐1 receptor antagonist deficient (IL‐1Ra‐/‐) mice spontaneously developing a T cell‐ and interleukin (IL)‐17‐dependent severe arthritis, we found that the presence of microbiota is critical for disease development, since germ‐free IL‐1Ra‐/‐ mice did not develop arthritis at all. T cell production of IL‐1 and IL‐17 in response to anti‐CD3 activating antibodies and Toll‐like receptor ligands was substantially disrupted in germ‐free IL‐1Ra‐/‐ mice compared to conventionally housed mice. The association of specific fecal microbiota of IL‐1Ra‐/‐ mice with arthritis development was assessed using multiplex pyrosequencing of the V5 and V6 hyper‐variable regions of 16S rRNA with a 454 FLX instrument (Roche). Preliminary analysis revealed strong association between the genus Helicobacter and the development of arthritis. The feasibility of microbiota modulation as a therapeutic approach during established arthritis was assessed by a prebiotic diet containing 2.5% short‐chain galacto‐ and long‐chain fructooligosaccharides (scGos:lcFos, 9:1), known to selectively support growth of commensal Bifidobacteria and Lactobacilli. This dietary intervention significantly suppressed the severity of arthritis and the accompanying joint destruction in IL‐1Ra‐/‐ mice and reduced the expression of T‐bet and RORγt, the Th1 and Th17‐related transcription factors. Furthermore, scGos/lcFos diet significantly improved bone mineral density and bone mineral content. Upon pyrosequencing, the relative abundance of Helicobacter in intestinal microbiota appeared to be reduced. Further analysis is currently ongoing. This study was financially supported by the Dutch government grant of Top Institute Pharma.
Upper digestive tract microbiome diversity is associated with total mortality in a prospective cohort study in China Christian C. Abnet1, Jianxin Shi1, Vanja Klepac‐Ceraj2, Bruce J. Paster2, Mitchell H. Gail1, Bruce A. Dye3, Wen‐Qiang Wei4, Jin‐Hu Fan4, You‐Lin Qiao4, Sanford M. Dawsey1, Neal D. Freedman1 1
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA; 2Forsyth Institute, Boston, MA; 3Centers for Disease Control and Prevention/National Center for Health Statistics, Hyattsville, MD; 4Cancer Institute, Chinese Academy of Medical Sciences, Beijing, PRC.
[email protected] We previously showed that tooth loss is associated with increased risk of total mortality in a population‐based cohort study in central China. Here we tested whether upper aerodigestive tract (UDT) microbiome diversity is associated with total mortality among 659 subjects aged 40‐65 years that were followed for 9 years after biosample collection. We characterized individual upper digestive tract microbiome using the HOMIM DNA microarray and used a unifrac distance matrix to conduct unweighted pair group method with arithmetic mean cluster analysis and principal coordinate analysis (PCA). We compared cluster residence and principle coordinate scores using Cox proportional hazards models adjusted for potential confounders including age, sex, tobacco smoking, and alcohol drinking. Subjects had a median of 38 species in their UDT microbiome and subjects that died (N=68) had median of 2 fewer species than those that did not. We found support for 3 clusters in the distance matrix and found a significant (Fisher exact P = 0.019) difference in the distribution of deaths. Subjects in one cluster had a hazard ratio (HR) (95% confidence interval) of 2.02 (1.19‐3.43) compared to the largest cluster. Furthermore, a one standard deviation difference in PCA vector 3 score carried an HR (95% CI) of 1.17 (1.01‐1.35) or a significant 17% increase in the risk of death. Our study shows that UDT microbiome diversity is associated with risk of total mortality in a prospective cohort and that it was independent of many potential confounders.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
Life on human surfaces: skin metagenomics. Alban Mathieu1-2, Tom C. Delmont1, Timothy M. Vogel1, Patrick Robe2, Renaud Nalin2 and Pascal Simonet1 Environmental Microbial Genomics, Laboratoire Ampere, Ecole Centrale de Lyon, Université de Lyon, 36 Avenue Guy de Collongue, 69134 Ecully, France. 1
2
LibraGen, 3 Rue des Satellites, 31400 Toulouse, France.
Human skin microbial communities live at the interface with the surrounding environment. Some aspects of this microbiota are already known to affect human health. Here, we present our metagenomic analysis of two human skin metagenomes. A sufficient quantity of DNA was recovered to provide the first metagenomic study of human skin microbiota from two individuals at two subsequent time periods without a DNA amplification step. The metagenomes from the two sample times were relatively consistent, however significant differences were observed between the two individuals. The metagenome datasets were used to evaluate the functional potential of human skin microbiota as function of individual and temporal variations. These datasets from human skin microbiota were also compared to metagenomes from various other environments including human feces, and thus, demonstrated specific functional and taxonomical distributions. These specific differences (e.g., biofilms formation, antibiotic resistance) can help understand the life style of these communities and their potential role in human health.
Association
of
cutaneous
microbiota
with
psoriasis
Alexander
V.
Alekseyenko1,
Guillermo
I.
Perez
Perez
1,
Aieska D'Souza1,
Bruce
Strober2,
Barbara
Methe3,
Martin
J.
Blaser1
1
New
York
University
Langone
Medical
Center,
New
York
NY,
10016.
University
of
Connecticut
School
of
Medicine,
Farmington,
CT,
06030
3 JCVI,
Rockville,
MD.
[email protected]
2
Psoriasis
is
a
common
chronic
inflammatory
disease
of
the
skin.
We
sought
to
characterize
the
population
of
bacteria
overlaying
cutaneous
psoriatic
lesions
(PL),
clinically
unaffected
contralateral
skin
from
psoriatic
patients
(PN),
and
similar
skin
loci
in
matched
healthy
control
subjects
(CC).
Using
16S
rRNA
high‐throughput
sequencing
we
assayed
the
cutaneous
microbiome
for
51
such
triplets
including
subjects
of
both
genders,
different
age
groups
(18‐81
yo)
and
ethnicities,
and
multiple
body
sites.
We
observe
increasing
intra‐group
(Unifrac)
beta‐diversity
in
the
psoriasis
specimens
(diversity
CC 0.05) among groups, which indicates that the consumption of PDX and SCF did not alter overall fecal bacterial diversity. The consumption of PDX and SCF led to increased (P < 0.05) fecal Clostridiaceae and Veillonellaceae, and decreased Eubacteriaceae. Faecalibacterium prausnitzii was increased (P < 0.05) after consumption of both fibers. Principal component analysis (PCA) clearly indicated distinct clustering of individuals consuming novel fibers as compared to those consuming NFC. The PCA loading plot indicated strong correlation of fecal SCFA with Lachnospiraceae, Ruminococcaceae, and Eubacteriaceae, suggesting that these families were the major producers of SCFA in our human subjects. Furthermore, distinct separation of total SCFA and metabolites of protein fermentation were observed. In conclusion, data demonstrated a beneficial shift in the gut microbiome of adults consuming PDX and SCF.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
EBI Metagenomics: Studying the Functions of Metagenomes. Christopher I Hunter, Sarah Hunter EMBL‐EBI, Interpro, Cambridge, CB102AY, United Kingdom
[email protected] The EBI metagenomics portal (www.ebi.ac.uk/metagenomics) has been borne of the need to collate and integrate existing EBI resources currently used by metagenomics researchers, such as the European Nucleotide Archive, InterPro and UniProtKB, into a centralised and user friendly portal. Here we present the current analysis pipeline. To illustrate its use, we analysed a set of Human gut microbiome sequences from an obese and lean twins study published by Turnbaugh et al 2009(1). These data show ~50% of reads (Roche 454) per dataset are found to have matches to the InterPro database. The analysis results are in line with those reported by the authors. We also present future additions planned for the pipeline and an example of the analysis summary. Since this is work in progress, we are very keen to canvas potential users for their views and opinions on how this resource should evolve in order to reach our goal of becoming the European focal point of metagenomic data archiving and analysis. (1) Turnbaugh, P J, et al. A core gut microbiome in obese and lean twins. Nature 2009. 457, 480‐484.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
The Data Analysis and Coordination Center for the Human Microbiome Project Heather Huot Creasy and the Data Analysis and Coordination Center Institute for Genome Sciences, 801 West Baltimore St, Baltimore MD 21201
[email protected] The NIH Common Fund Human Microbiome Project (HMP) has produced unprecedented amounts of information about the microbial communities living on and within humans. The Data Analysis and Coordination Center (DACC) of the HMP provides an infrastructure to enable the scientific community to access, analyze and interpret human microbiome data, with the ultimate goal of advancing our understanding of human health. In addition, the DACC is actively involved in working with the larger scientific community on development of new analysis tools, and in engaging the research community with outreach and training on the use of resources generated by the HMP. To this end, the DACC provides a web resource available at hmpdacc.org. This presentation will describe recent developments to this resource including the release of i) terabytes of sequence data from reference genomes, metagenomic 16s samples, and metagenomic wgs data, ii) MixS‐ compliant metadata associated with these datasets, iii) Illumina‐based and Illumina/454‐hybrid‐ based gene indices and clustered gene sets, iv) metabolic reconstruction analyses, and v) community profiling using both 16S and wgs data. We are actively implementing step‐by‐step tutorials called “walkthroughs” that will enable researchers, in particular those without extensive bioinformatics experience, to utilize HMP‐related tools and resources to reproduce HMP analyses using either HMP‐ generated or other data as input. Future directions of the web resource will also be described.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
GA‐map™ ‐ a rapid, comprehensive gut microbiota analysis Heidi Vebø1, Monika Sekelja1, Selma Kreso1, Knut Rudi1,2, Morten L. Isaksen1 1. Genetic Analysis AS, Nycoveien 2, Oslo, Norway. 2. University of Life Sciences, Aas, Norway mi@genet‐analysis.com As the awareness of the effect of the gut microbiota on health is increasing, so is the need to find tools to study changes in the gut microbiota in a rapid, cost‐effective and high throughput format. Several methods are available, and each has their own strengths and weaknesses. Genetic Analysis AS has developed GA‐map™, a proprietary technology that can be used in rapid analysis of a large number of fecal samples in a cost‐effective way. The results from the assay can be directly linked to changes in the gut microbiota, and used to test a high number of samples rapidly. By using intelligent design of specific probes, the assay gives direct, quantitative signals that reflect the presence of a wide range of bacteria in the sample. The technology has been demonstrated as a useful tool for assessing health‐conditions like allergy, Necrotizing Enterocolitis (NEC) and, Inflammatory Bowel Disease (IBD), and examples from work in these areas will be given.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
Intestinal microbiota in healthy adults: dimensions of the common core and relation to intestinal symptoms Jonna Jalanka‐Tuovinen1 Anne Salonen1, Jarkko Salojärvi1, Leo Lahti, Airi Palva1, and Willem M. de Vos1,2 1) Department of Veterinary Biosciences, Microbiology, University of Helsinki, Helsinki, Finland, 2) Laboratory of Microbiology, Wageningen University, Wageningen, The Netherlands
[email protected]
Trillions of microbes in our gastrointestinal tract from a complex ecosystem (microbiota), characterised by high individuality and immense metabolic capacity. The GI microbiota essentially contributes to our health and alterations to it have been associated with many disease states. Advances in high‐throughput methods enable the characterization of the intestinal microbial core, i.e. the bacteria we all share. Here, we studied the presence and abundance of phylotypes from over 100 healthy individuals with phylogenetic microarray, HITChip. In order to define the common core we coupled the analysis with a novel computational approach and showed that the microbial core size is dependent on the analysis depth and the prevalence but also on the health status of the host. We estimate that approximately 30% of the detected over 1000 phylotypes are shared between the studied healthy subjects. These findings suggest that we share a larger part of our intestinal phylotypes than previously thought but as they represent highly variable proportions of the total community, many of them often remain undetected. In order to characterize the healthy intestine a selected subjects recorded a health related quality of life questionnaire, which enabled us to correlate minor intestinal symptoms to the microbial composition. We identified significant correlations between the microbiota and common intestinal symptoms, including abdominal pain and bloating. These novel findings will help to facilitate a conceptual definition of the common microbial core of healthy individuals and benchmark how minor intestinal symptoms experienced by these subjects affect the intestinal microbiota.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
Microbial diversity is highly correlated with the Healthy Food Diversity Index Ian B. Jeffery1 , Marcus J. Claesson1,2, Hugh Harris1, Susana Conde, Anthony P. Fitzgerald, and Paul W. O’Toole1,2 on behalf of The ELDERMET Consortium¥ 1
Dept. of Microbiology Alimentary Pharmabiotic Centre 3 Department of Epidemiology & Public Health University College Cork, Ireland *
[email protected] 2
¥ http://eldermet.ucc.ie It is well known that diet strongly influences human health. It is also becoming increasingly clear that dietary modulation of the gut microbiota plays a large part in this effect. A recent study by Wu et al. (2011) showed that diets rich in animal protein led to a markedly higher abundance of Bacteroides species and depletion of Prevotella species, when compared to diet low in animal products and high in fruit and vegetables. Here we examine further the association between the microbiota and diet. Dietary data for 168 elderly subjects was collected through a semi-quantitative, 147-item, food frequency questionnaire (FFQ), weighted by 10 consumption frequencies. This was paired with 16S rRNA pyrotags sequenced from DNA extracted from feacal samples. Four dietary patterns were identified across four community locations. The diets could be described as combinations of low to high fat and low to high fibre with the most discriminating food types being vegetables, fruit and meat. The Prevotella to Bacteroides ratios were highest in the dietary group with the highest consumption of fruit and vegetables and the lowest consumption of meat. The Healthy Food Diversity index (HFD, Drescher LS et al, 2007) was calculated for each subject and was found to be significantly positively
correlated with microbiota diversity indices, suggesting that a healthy, diverse diet promotes a more diverse gut microbiota.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
Functional Repercussions of Subclinical Intestinal Dysbiosis In Unaffected Relatives Of Crohn’s Disease Patients Joossens Marie, Lepage Patricia, Mayeur Camille, Machiels Kathleen, Thomas Muriel, Raes Jeroen, Rutgeerts Paul, Vermeire Séverine, Doré Joël
[email protected]
D‐ and L‐lactate are bacterial metabolites that are not recovered in feces of healthy subjects as they are converted to butyrate and other end‐products by bacterial cross‐feeding. Some publications report however, on the recovery of D‐ and L‐lactate in samples of ulcerative colitis (UC) patients. As subclinical dysbiosis has also been reported in unaffected relatives of Crohn’s disease (CD) patients and UC patients, we studied if there might be a functional overlap between the dysbalanced microbiota of inflammatory bowel disease (IBD) patients and that of their unaffected relatives. In a cohort of families with UC and/or CD patients we studied 7 UC patients, 11 CD patients, 26 unaffected relatives and compared them with 4 healthy controls. D‐ and L‐lactate were measured in their fecal samples using D/L‐lactic acid enzymatic kits (Biosentec, France). From the same fecal samples, we extracted total bacterial DNA to also analyze the bacterial composition using pyro‐ sequencing of the amplified 16 rDNA. Very low quantities of fecal D‐ and L‐lactate (median amount:1,05mM and 0,79mM respectively) were detected in 2 of the CD patients (18%), 1 of the UC patients (14%) and 5 of their unaffected relatives (19%) compared to none of the controls (ns). However, in one UC patient we measured 8,69mM D‐lactate and 27,99mM L‐lactate. We detected elevated levels of fecal D‐ and L‐lactate in one UC patient. In a next step we will assess correlations between the presence of D‐ and L‐lactate in fecal samples and the composition of the microbiota.
2012 Human Microbiome International Conference – Paris, France, March 19‐21 2012
Anti‐inflammatory properties of commensal Steptococcus salivarius on human intestinal epithelial cells and in murine TNBS‐induced colitis model Ghalia Kaci*, Catherine Daniel, Bruno Pot, Joël Doré, S. Dusko Ehrlich, Pierre Renault, Hervé Blottière and Christine Delorme INRA, UMR1319 Micalis, F‐78350, France
[email protected] The commensal bacteria Streptococcus salivarius is one of the earliest colonizers of human mucosal surfaces few hours after birth. This species remains prevalent in the oral cavity and sub‐ prevalent in the digestive tract and may therefore contribute to the establishment of immune homeostasis and the regulation of host inflammatory responses. S. salivarius was shown to influence the inflammatory response triggered by periodontopathogens and attenuate NF‐κB activation in bronchial epithelial cells, suggesting a role of this bacterium in inflammation. We have recently reported properties of S. salivarius, which significantly reduced the activation of NF‐κB and IL‐8 secretion in several lines of intestinal epithelial and immune cells by the release of a low‐molecular‐ weight soluble factor {Kaci et al., 2011}. The active compound that harbored inhibitory effect on TNF‐ α induced NF‐κB activation in HT29 cells, has been partially purified in hydrophobic
