Post on 26-Dec-2015
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Metagenomics
Prof:Rui Alvesralves@cmb.udl.es973702406Dept Ciencies Mediques Basiques,1st Floor, Room 1.08Website of the Course:http://web.udl.es/usuaris/pg193845/Courses/Bioinformatics_2007/ Course: http://10.100.14.36/Student_Server/
Studying an organism
…ACTG…
>Dna
MAACTG…
>DNA Pol
MTC…
Stress
Measure Response
Find signatures for physiological dynamics in
genomic data
Diversity of Life on Earth
Described species: ~1.5 millions Predicted to exist: >30 millions Cultivate in the lab: ~thousands How do we know the genome of the species
we can not cultivate? How can we know if the genes that are
expressed in nature follow the same patterns as those in the lab?
Metagenomics
Metagenomics (also Environmental Genomics, Ecogenomics or Community Genomics) is the study of genetic material recovered directly from environmental samples.
Sampling in Metagenomics
Take a sample off of the environment
Isolate and amplify DNA/mRNA
Sequence it
Shotgun Sequencing
Restriction Enzymes
Computer assembly
ACT…GTC CTA …ATC … …GGGG
How do we know which genes belong to which genome????
How do we assemble them???
The Best Case Scenario
Coverage is enough to assemble independent genomes
What normally happens
Coverage is not enough and assembly is fragmentary
Worst Case Scenario: Some fragments can not be assigned
Down Side of Metagenomics
Often fragmentary Often highly divergent Rarely any known activity No chromosomal
placement No organism of origin Ab initio ORF predictions Huge data
Marine Metagenomics
Microbes account for more than 90% of ocean biomass, mediate all biochemical cycles in the oceans and are responsible for 98% of primary production in the sea.
Metagenomics is a breakthrough sequencing approach to examine the open-space microbial species without the need for isolation and lab cultivation of individual species.
PI Larry Smarr
Paul Gilna Ex. Dir.
PI Larry Smarr
Marine Genome Sequencing ProjectMeasuring the Genetic Diversity of Ocean Microbes
Sorcerer II Data from this area has already reach to 10% of GenBank.
The Entire Data Will Double Number of Proteins in Embank!
Sample Metadata from GOS Site Metadata
Location (lat/long, water depth)
Site characterization (finite list of types plus “other”)
Site description (free text)
Country
Sampling Metadata Sample collection date/time
Sampling depth
Conditions at time of sampling (e.g., stormy, surface temperature)
Sample physical/chemical measurements (T (oC), S (ppt), chl a (mg m-3), etc)
“author”
Experimental Parameters Filter size
Insert size
Flat FileServerFarm
W E
B
PO
RT
AL
Traditional
User
Response
Request
DedicatedCompute Farm(1000 CPUs)
TeraGrid: Cyberinfrastructure Backplane(scheduled activities, e.g. all by all comparison)
(10000s of CPUs)
Data-BaseFarm
10 GigE Fabric
Calit2’s Direct Access Core Architecture Will Create Next Generation Metagenomics Server
Source: Phil Papadopoulos, SDSC, Calit2+
Web
Se
rvic
es
Sargasso Sea Data
Sorcerer II Expedition (GOS)
JGI Community Sequencing Project
Moore Marine Microbial Project
NASA Goddard Satellite Data
Community Microbial Metagenomics Data
Web(other service)
Local Cluster
LocalEnvironment
DirectAccess LambdaCnxns
Marine Metagenomics
Who is there?
Drug discovery
Environmental surveyMicrobial genetic survey
Microbial genomic survey
Symbiosis
Organism discovery
Marine conservation
Evolution study
Bioenergy discovery
Endosymbiosis
Biogeochemistry mapping
Metabolic pathway discovery
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Nutrigenomics
Prof:Rui Alvesralves@cmb.udl.es973702406Dept Ciencies Mediques Basiques,1st Floor, Room 1.08Website of the Course:http://web.udl.es/usuaris/pg193845/Courses/Bioinformatics_2007/ Course: http://10.100.14.36/Student_Server/
04/19/23 21
What is Nutrigenomics?
Nutrigenomics is the science that examines the response of individuals to food compounds using post-genomic and related technologies.
The long-term aim of nutrigenomics is to understand how the whole body responds to real foods using an integrated approach.
Studies using this approach can examine people (i.e. populations, sub-populations - based on genes or disease - and individuals), food, life-stage and life-style without preconceived ideas.
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Why is Nutrigenomics important?
Most non-genetic diseases are behaviorally related.
E. g. Last year in the world, heart disease was responsible for a fraction of deaths comparable to that caused by infectious diseases. Diabetes, obesity growing!!! Of course genes are a factor.
Finding the right combination of nutrients for each genotype can help in changing behavior and preventing many of these diseases.
This combination may change with age, sex!!
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Problem 1: Nutrition – tasty + complex
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Genes – Lifestyle – Calories
100
50
0
% Energy
Low-fat meatChickenEggsFish
FruitVegetables (carrots)NutsHoney
100
50
0
% Energy
FruitVegetablesBeans
MeatChickenFish
GrainMilk/-productsIsolated CarbohydratesIsolated Fat/OilAlcohol
1.200.000 Generations between feast en famine
Paleolithic era
2-3 Generations in energy abundance
Modern Times
The same genes – The changed diet
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Molecular nutrition
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Optimal Nutrition
Lifestyle
Individual genotype Functional phenotype
Problem 2:Our “gene passports” and nutrition
AA AB BB
ImprovementMaintenance
of Health
“Eat right for your genotype??”
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Personalized diets?
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Energy homeostasis
Energy homeostasis
Nutrient absorptionNutrient
absorption
Cell proliferation
Cell proliferation
Nutritional factors
Transcription factors
Gene transcription
Nutrients acts as dietary signals
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Transcription-factor pathways mediating nutrient-gene interaction
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A key instrument in Nutrigenomics research: The GeneChip® System
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ppm0123456789
Gene
Protein
MetaboliteTargets
andBiomarkers
Targets and
Biomarkers
BiostatisticsBioinfomatics
BiostatisticsBioinfomatics
gene
inde
x
prot
ein
inde
x
metabolite index
Sample Types:
• 10 ApoE3 mice• 10 wildtype mice
• liver tissue• plasma• urine
Figure 1. A typical Systems Biology strategy for study of atherosclerosis [1] usinga transgenic ApoE3 Leiden mouse model.
PredispositionGenotype
Prognosticmarkers
Diagnosticmarkers
Changes in pathway dynamicsto maintain homeostasis
SurrogateBiomarkers
Late biomarkersof disease
Early biomarkersof diseaseOnset of
disease
Nutritional Systems Biology
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Nutrigenomics
Target GenesMechanisms
Pathways
Target GenesMechanisms
Pathways
SignaturesProfiles
Biomarkers
SignaturesProfiles
Biomarkers
FoodsNutrition
Molecular Nutrition& Genomics
Molecular Nutrition& Genomics
NutritionalSystems Biology
NutritionalSystems Biology
•Identification of dietary signals•Identification of dietary sensors•Identification of target genes•Reconstruction of signaling pathways
•Identification of dietary signals•Identification of dietary sensors•Identification of target genes•Reconstruction of signaling pathways
•Measurement of stress signatures•Identification of early biomarkers•Measurement of stress signatures•Identification of early biomarkers
Small research groupsSmall budgets
Large research consortiaBig money
Complexity
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“Molecular Nutrition & Genomics” The strategy of Nutrigenomics
80-100000proteins
20-25000 genes
100000 transcripts
50000 (?)metabolites
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Integration of enabling technologies in nutrigenomics
Microarray & SAGE
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Two Strategies(1) The traditional hypothesis-driven approach: specific genes and
proteins, the expression of which is influenced by nutrients, are identified using genomics tools — such as transcriptomics, proteomics and metabolomics — which subsequently allows the regulatory pathways through which diet influences homeostasis to be identified . Transgenic mouse models and cellular models are essential tools .
provide us with detailed molecular data on the interaction between nutrition and the genome .
(2) The SYSTEMS BIOLOGY approach: gene, protein and metabolite signatures that are associated with specific nutrients, or nutritional regimes, are catalogued, and might provide ‘early warning’molecular
biomarkers for nutrient-induced changes to homeostasis. Be more important for human nutrition, given the difficulty of collecting tissue samples from ‘healthy’ individuals.
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LIPGENLipids & genes
(EU, 14M€)
DIOGENESobesity
(EU, 12M€)
Innovative Cluster NutrigenomicsChronic metabolic stress
(Dutch, 21M€)
EARNESTearly life nutrition
(EU, 14M€)
Linking to other EU programs
Lipid metabolism
Life stage nutrition
Risk Benefit analysis
Metabolic health
ProliferationDifferentiation
Apoptosis
Inflammation
Muscle insulin resistance
Nutrigenetics
Early biomarkers
Periconceptualnutrition
Nuclear transcription
factors
Systems biology
Host-microbeinteraction
Gut Health
Absorption
Genetic epidemiology
Toxicogenomics
Metabolic stress
Adipocytefat oxidation
Diabetes II
Carotenoids
Lipid metabolism
Life stage nutrition
Risk Benefit analysis
Metabolic health
ProliferationDifferentiation
Apoptosis
Inflammation
Muscle insulin resistance
Nutrigenetics
Early biomarkers
Periconceptualnutrition
Nuclear transcription
factors
Systems biology
Host-microbeinteraction
Gut Health
Absorption
Genetic epidemiology
Toxicogenomics
Metabolic stress
Adipocytefat oxidation
Diabetes II
Carotenoids
NuGO
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(1) Nutrigenomics researchers must know the challenge of understanding polygenic diet related diseases.
(2) Short-term goals:
1. to identify the dietary signals.
2. to elucidate the dietary sensor mechanisms.
3. to characterize the target genes of these sensors.
4. to understand the interaction between these signalling pathways and pro-inflammatory signalling to search for sensitizing genotypes.
5. to find ‘signatures’ (gene/protein expression and metabolite profiles).
Conclusion and future perspective
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(3) Long-term goals:
Nutrigenomics is to help to understand how we can use nutrition to prevent many of the same diseases for which pharmacogenomics is attempting to identify cures.
SNP database will be effect on disease risk.
Future personalized diets