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Transcript of Metagenomics of Microbial Communities Scott Sproule Cam MacMillan Daniel Hann.
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Metagenomics of Microbial Communities
Scott SprouleCam MacMillanDaniel Hann
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OutlineContext- A brief history of microbiology- A brief history of genomics- Defining metagenomicsMetagenomics - Transcending genomics- Accurate diversity measurementsTwo approaches of metagenomics- Sequence based approach- Function based approachEnvironmental analysis- Marine- SoilApplications of Metagenomics- Industrial - Agriculture & Renewable Energy- Environmental remediation- Life sciencesConclusion
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Context
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Date Contributor Contribution
1703 Robert Hooke Observed Cells
1677 Antonie van Veeuwenhoek Observed microbes
1776 Edward Jenner Vaccine
1862 Louis Pasteur Germ Theory
1875 Ferdinand J. Cohn Classification of Bacteria
1881 Robert Koch Bacteria & Disease
1928 Frederick Griffith Transformation
1950’s
Jonas Salk Advances in cell culturing
1963 Jacob & Monod Operon concept
1973 Cohen, Chang, Helling, & Boyer
Plasmids as vectors
1986 Kary Mullis Polymerase chain reaction
Microbiology: Perspective
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Main Techniques
Culturing Techniques Microscopic Techniques
- Direct observation- Combine with
- Staining- Isotopes- Flourescence
- Growing- Isolation- Examination- Manipulation- experimentation
Inconsistent estimates of diversity and organisms numbers
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Accounting for Inconsistencies
- How much were they missing?
- What were they missing?
- Why were they missing it?
“The Great Plate Count Anomaly”
It was clear that there were many viable cells that could not be cultured
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“Unculturability”
Environmental- Nutritional factors- Signaling factors- Essential factors- Artificial reproduction
difficult
Bacteria- Specific requirements- Competition- Community structure- Defense mechanisms
“Can we culture the unculturable?
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Genome
- Common all living things on earth
- A universal language
- An instruction manual
- A toolbox
- A record of history
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Genomics
the study of whole genomes
Nucleotides DNA Genes Genomes
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History of Genomics
Date Contributor Contribution
1858 Darwin Natural selection
1865 Mendel Genetic inheritance
1941 Beagle and Tatum One gene, one enzyme
1944 Avery, MacLeod, & McCarty
DNA genetic material
1946 Lederberg & Tatum Bacterial recombination
1953 Watson & Crick Double helix
1969 Bell laboratories UNIX
1974 Cerg & Kahn TCP protocol
1977 Sanger Sanger sequencing
1982 GenBank Online database
1990 Altshul BLAST
1995 Venter & Celera Corp Shotgun sequencing
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Rapid sequencing of whole genomes
The pinnacle of genomics?
Metagenomics transcends genomics
Multiple genome level
Genomics Today
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Metagenomics
Meta-analysis – combination of separate analysis
Genomics – analysis of an organisms genetic material
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What is metagenomics?Study of the collection of microbial genomes or genome fragments through direct extraction
A culture independent technique that can provide meta-analytic level information about:
- Population structure- Genetic Diversity- Functional elements- Novel genetic material
A synthesis of a number of fields:- Molecular Genetics- Microbiology- Bioinformatics- Population Genetics- Computer science
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Applying Metagenomics to Microbial Communities
Traditional methods of quantifying microbial diversity- Sample environments independently- Isolate each species through culturing
techniques- Characterize through biochemical &
sequencing techniques
Realistic?- Very labour intensive- Time estimate: 100’s of years- Incredibly expensive $$$$$$- Most organisms can not currently be be
isolated through culture
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Microorganisms
Are Everywhere!
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Scratching the surface
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Tools of Metagenomics- Cloning techniques- PCR- Cutting edge sequencing techniques- Bioinformatics- Open source databases
- Genbank- Protein Database- TreeBASE
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GenBank - “An annotated collection of all publicly available nucleotide and amino acid sequences.” --NCBI
Growth of GenBank
Steep hill to climb!
Doubling every 18 months!
Founded: 1982
Shotgun Sequencing: 1995
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Approaches to metagenomics?
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Questions for metagenomics
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Analysis
Two main approaches
(1) Sequence driven
- What genes are there
(2) Function driven
- What the genes do
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Sequence driven approaches- Data collection- Relies on conserved DNA- Phylogenic analysis- Used to measure biological
diversity
Functional driven approaches- Functional screening- Can identify novel genes- Relies on gene expression
- Proteins
Extract DNA
Metagenomic Process
Determine what the genes are
Determine what the genes do
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Sequence-Based Approach
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Sequencing
• One way to classify metagenomic fragments• Relies on nucleotide diversity analysis
– Discriminate between species
Seq. A GACTACGATCCGTATACGCACA--GGTTCAGAC|| ||||| ||||||||||||| |||||||||
Seq. B. GAATACGAGCCGTATACGCACACAGGTTCAGA
• Requires use of online databases– Ex: BLAST in GenBank
Compares “unknown to known”
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Restrictions
Genomics Metagenomics
Whole Genome Sequenced
Know Species of Origination
Many DNA elements Identified
✔ ✖
✔
✔
✖✖
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Sequence Metagenomics
• Not necessary to determine species of origin
• Obtain large volume of data ~ Less redundant
• Fragment’s = 20bp – 700bp
• Assembled sequence reads don’t exceed 5000 bp
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Random Shotgun Sequencing
1. Library construction
a. isolate DNA
b. fragment DNA
c. clone DNA
2. Random Sequencing Phase
a. Automated pyrosequencing DNA
VECTORACTGTTC...
3. Assembly
a. assemble sequences
b. close gaps
C. edit sequence4. Annotation
AndPublication
Missassemblies?
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Random Sequencing
Objective– To estimate bacterial biodiversity ~ Species Richness– Identify 1000’s of prokaryotic, viral & eukaryotic species– Mass amounts of genomic data obtained– Does not depend on PCR– Put sequence in computer BLAST
– Studies in:• Sea water• Soil microbial mats• Dead whale carcass• Feces etc.• Organism level (microbiome)
– Microorganisms are Everywhere!
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Sequence Specific: Phylogenic
• Look at evolutionary relationships
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Key Challenge
• Analysis based on evolutionarily conserved marker sequences
Want– High conservation across species– Slight & measureable changes over millions of
years
What to look for?
16S rRNA
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16S rRNA
Value• Vital for translation
– Essential• Short• Conserved within a species• Different between different species• Very slow mutation rate
Species Concept- Sequence based arbitrary - ~ Consensus: ~97% identity = species- Changing all the time
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Screen for 16S rRNA sequence
• Extract DNA• Construct clone
library• Ex BAC cloning
• Screen using sequence specific primers
• When desired fragment is found• Sequence &
compare
Alignment represents a hypothesis
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Function Based Approach
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Sample
Genomic DNA extraction
DNA sheared
Plasmid vector
Transformation
Functional screening
Functional Approach: Overview
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DNA Extraction and Isolation
Removal of contaminants
Aspects of Sample
Blender Centrifugation
Cell purification
Cell lysis
DNA Isolation & Restriction Digest
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Cloning & Transformation
Random Fragmentscloned into expressionvectors
Expression vectorstransfected into broad expression hosts
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Plasmid Expression vectors
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Functional Screening
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Treasure Hunting
Looking for novel genes
Biological tool boxes
Detergents- Proteases- Lipases- Esterase’s
Antibiotics- Novel antibiotics- Not synthetic- Mutate the antibiotics
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- Microbes = 90% of marine biomass
Marine Metagenomics
- 98% of Primary Producers in Sea
- .001-.1% are cultivable
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Craig Venter
Ocean Exploration
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• Ocean exploration genome project in aims of assessing the microbial diversity of marine microorganisms
• 7.7 million sequence reads 44 different samples 41 sites
• Surface water at 320km intervals
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Sample Collection
• Determine physical characteristics of sample site – Salinity, pH, depth, dissolved O2,
temperature– Filtered & storage
• Characterize Genetic Material– DNA Isolation– Constructing a Library– Automated Sequencing
• Metagenomic Analysis
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Discoveries
• First twelve hours in Sargasso Sea– Tripled the number of known prokaryotes on earth
• Six million new genes – 1.3 million new genes + 50 000 species from single site
• Tens of thousands of new protein families
• 782 rhodopsin-like photoreceptors– Previously only found in Archaea
• Unexpected links between genetics & environment– Different rhodopsin proteins in open ocean vs coast line
Better understanding of key biological processes?– New ideas for alternative energy production?– Solutions to deal with climate change?
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Components
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Soil Metagenomics
Soil is very diverse- Nutrients- Moisture- pH- Organic- Oxygen- Temperature- Surface vs. Subsurface
Elusive- Poor recovery rate- Nuclease- Cell bias to lysis techniques- Different methods yield
dramatically different estimates of diversity and organism number
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Soil Diversity
The number of prokaryotic species found in a single soil sample exceeds the number of known cultured prokaryotes
40X more diverse than marine
Soil is very diverse- Nutrients- Moisture- pH- Organic- Oxygen- temperature
Estimates:
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Accounting for different extraction methods
Soil Requires more Complicated Approach
Variability in Extraction Methods
How much are we still missing?
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Other Metagenomic Hot Spots…
Whale Carcass
Wastewater
Human Gut
Feces
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Applications of Metagenomics
“The metagenome provides a potentially inexhaustible genetic resource for biomolecules of potential utility in a variety of industries”
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Applications of Metagenomics- Metagenomics offers potential solutions to some of the most complex
medical, environmental, agricultural and economic challenges of today
- Biotechnological potential of uncultivated bacteria might be accessible by directly cloning DNA sequences retrieved from the environment
Information on why certain organisms
are unculturable
Culture these organisms
Discover novel Pathways
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Industrial Applications
• Novel enzymes rare through culturing
• Novelty: Avoid infringing on a competitor’s intellectual rights• Bacillus Protease Novo
• Hundreds of variations with a single AA substituted
• Enzymes are vital for many different industries and their sales are estimated at $2.3 billion in 2003.
• Food applications, detergents, textiles, agriculture, pulp/paper and other chemicals
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Industrial Applications
- Temperature
- pH
- Pressure
- Speed
- Turnover
Search for the “Ideal” bio-catalyst
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Environmental Remediation
Environmental Contamination • Toxic metals• Fossil fuels• Chemicals• Xenobiotics
Microorganisms can interact withcontaminants
• Oxidize• Bind• Transform• Immobilize
Metagenomic searches forgenes & proteins involved
Picking on Alberta: Tar Sands
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Agriculture– Detecting diseases in livestock, crops and other
products
– Soils rich in microbial communities.
– Communities very complex, poorly understood and their intimacy with crops means they are of economic importance• nutrient cycling, nitrogen fixation, sequestering
metals– Understanding soil composition Enhanced farming
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Renewable Energy
• Typically derived from biomass sources
• Cellulose and other non-edible parts of plants transformed into biofuels
• Transform cellulose into usable ethanol, methanol• Ex: Cellulosic ethanol
• Produce energy sources such as hydrogen and methane
• Capture and store these by-products
• Metagenomics approaches for new, efficient ways of producing energy sources
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Renewable Energy
Searching mircobial communities for biomolecules that can be used as energy
Looking in unlikely places
Cow Rumen:
- Cellulose digestion Methane
- Cleaner methane
- Metagenomic analysis for compounds involved in this reaction
Ex: Bio- Alcohols, Bio-Diseases, Oils, etc….
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Human Health
– The microbiome: The relationship between the human body and the microbial communities will lead to new methods for diagnosing, treating and preventing diseases
– Being used to sequence the microbial communities from ~18 body sites from 250 individuals to determine if changes to the human microbiome can be correlated with human health.
– Drugs from microbe-derived compounds: Look for function• metagenomics searches
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Metagenomic Approach to Microbiome
- Microbiome very influential to human health
- What do know know about the microbiome?
- Metagenomic approach tells us not very much
- Comparing microbiome of healty and non. Healthy
- Microbiome transplants?
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Future Directions
• New enzymes, antibiotics, and other reagents identified
• More exotic habitats can be intently studied
• Can only progress as library technology progresses, including sequencing technology
• Improved bioinformatics will quicken library profile analysis
• Investigating ancient DNA remnants
• Discoveries such as phylogenic tags (rRNA genes, etc)
• Learning novel pathways will lead to knowledge about the current nonculturable bacteria to then learning to culture these systems
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Conclusion