Microbiology has experienced a transformation during the last 25 years that has altered microbiologists' view of microorganisms and how to study them. The realization that most microorganisms cannot be grown readily in pure culture forced microbiologists to question their belief that the microbial world had been conquered. We were forced to replace this belief with an acknowledgment of the extent of our ignorance about the range of metabolic and organismal diversity.

1. METAGENOMICS &
MICROBIAL IDENTIFICATION
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2. INTRODUCTION
• The term “Metagenomics" was first used by Jo
Handelsman in 1998.
• Also called Environmental genomics or Microbial
ecogenomics
• “Bioprospecting” microbial habitats for novel
products and processes
• Determine ecological/biogeochemical role of
microbes in unique habitats
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3. MICROBES ARE BENEFICIAL
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4. Microbiology Till Metagenomics
• Until recently, microbiology
research required culture-
based techniques.
• <1% of all microbes can be
cultured (Sleator et al. 2008)
• Traditional techniques have
left us with a biased and
incredibly incomplete
understanding of microbes.
– Sequence the genome of one
organism at a time
– Use cultures to isolate
microbe of interest
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5. • Extract sequence data from microbial communities
as they exist in nature
• Bypass the need for culture techniques
• Opened new avenues of research
• Providing access to far more microbial diversity
than has been viewed in the petri dish.
DIFFERENT ASPECTS IN
METAGENOMICS
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6. 1. Site selection
2. Sample collection
3. Filtration
• Recording metadata
4. DNA extraction
• DNA enrichment
5. Sequencing
1. Ribotyping
2. Shotgun sequencing
6. Assembly
7. Binning
8. Annotation
SCHEMATIC OVERVIEW OF THE
METAGENOMICS
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7. 1.SITE SELECTION
– Collect more information about the habitat (physical,
chemical, and ecological) so more insight can be
derived from the metagenomic data.
– The discovery of the keystone species replies on
knowledge of the site.
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8. 2. SAMPLING
• Sample Size and Number of Samples
First and most crucial step
Rarefaction curves: estimate the fraction of
species sequenced
3. FILTERING
Size based separation
 Goals:
1. get as much as of what we need, and
2. leave out as much as what we don’t need
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9. • Recording Metadata
– Metadata are the ‘‘data about the data’’: where
the samples were taken from, when, and under
which conditions.
– It should be standard, comprehensive, and
amenable to computation.
– Genomic Standards Consortium: standardize the
description of genomes and metagenomes and
the exchange of genomic data and metadata
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10. 4. DNA EXTRACTION
DNA extraction based on sample type
• Invertebrate or plant fractionation or
selective lysis
• Soil projects physical separation a
& & isolation of cells
• Biopsies or ground water Multiple
displacement displacement
d amplification
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11. Techniques for the enrichment of
genomic DNA
• 5-Bromo-2-deoxyuridine (BrdU)
• Stable isotope probing (SIP)
• Metagenomic library enrichment using PCBs
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12. 10/21/2017 12

13. 5. Sequencing technology
• Classical method is Sanger’s sequencing
– Low error rate, long read length and large insert size
– Labor intensive cloning process in its associated bias against
genes toxic for the cloning host
Sequencing
1.Ribotyping
2. Shotgun
sequencing
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14. 16S rRNA
• Most commonly used molecular marker
• OTU (operational taxonomic units) based on 16S
rRNA gene
 organisms displaying 97 to 98% identity in this
gene to be part of the same OTU
• Rapid and cost-effective approaches for assessing
bacterial diversity and abundance.
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15. RIBOTYPING
• PCR amplification with primers that hybridize to highly
conserved regions in bacterial or archaeal 16S rRNA,
followed by cloning and Sequencing
• Phylogenetic analysis of 16S rRNA helps to reveal the
species diversity in a community
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16. Environmental Shotgun Sequencing
A
• Sampling from habitat
B
• filtering particles
C
• DNA extraction and
lysis
D
• cloning and library
E
• sequence the clones
F
• sequence assembly
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17. • ‘Metagenomic shot gun sequencing’ has gradually
shifted from classical Sanger sequencing to “Next
Generation Sequencing”.
• Second generation sequencing method
Pyrosequencing (eg: Roche 454 sequencing)
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18. Pyrosequencing
1
• Addition of one of the
four nucleotides
2
• Nucleotide addition
based on
complementarity
3
• Release of
pyrophosphate and
converted to ATP
4
• Luciferase causes
Light reaction
5
• Degradation by a
pyrase
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19. 6. ASSEMBLY
• The reads are assembled into contigs, and finally to
the whole genome
Strategiesfor
metagenomicsamples
Reference based assembly
( co assembly)
De-novo assembly
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20. • Reference based assembly
Softwares used
Newbler
AMOS
MIRA
Works well if the metagenomic dataset contains
sequences where closely related reference
genomes are available
• De-novo assembly
Requires larger computational resources
Based on de Bruijn graphs
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21. 7. BINNING
• Sorting of DNA sequences into groups that
represent an individual genome or genome from
closely related organisms.
Binning
Compositional binning
similarity-based binning
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22. • Involves the identify the protein-coding regions,
rRNA and tRNA genes
8. ANNOTATION
Feature
Prediction
Functional
annotation
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23. APPLICATIONS
• $2.3 billion in sales of industrial enzymes in 2003
• Discovery of novel enzymes and catalysts with
industrial uses by screening thousands of microbial
species simultaneously
• Looks for pharmacologically interesting genes (e.g.
antibiotics) that exist in organisms that cannot be
cultured
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24. ADVANTAGES OF METAGENOMICS
• Diversity patterns of microorganisms can be studied.
• Examining of genes/operons for desirable enzyme
candidates
• Examining of secretory, regulatory, and signal
transduction mechanisms associated with samples
or genes of interest.
• Examining metabolic pathways.
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25. • directed approach towards designing culture media
for the growth of previously-uncultured microbes.
• Examining genes that predominate in a given
environment compared to others.
• Metagenomic data can be leveraged towards
designing low- and high-throughput experiments
focused on defining the roles of genes and
microorganisms in the establishment of a dynamic
microbial community.
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26. LIMITATIONS OF METAGENOMICS
 Problems with DNA purification
 Sample contamination
 Issues with sequencing
 Immensity of metagenome
 Errors in assembly due to inter-species
similarities
 Difficulties in sequencing less well-represented
genomes
 Low Resolution
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27. REFERENCES
• Torsten Thomas, Jack Gilbert and Folker Meyer:
Metagenomics - a guide from sampling to data
analysis., Microbial Informatics and Experimentation
2012, 2:3
• John C. Wooley, Adam Godzik, Iddo Friedberg: A
Primer on Metagenomics., PLoS Computational
Biology 2010, 6(2):e1000667
• Joseph F. Petrosino, Sarah Highlander, Ruth Ann
Luna, Richard A. Gibbs, and James Versalovic:
Metagenomic Pyrosequencing and Microbial
Identification., Clin Chem. 2009, 55(5): 856–866
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28. • R.D. Sleator, C. Shortall and C. Hill:
Metagenomics., Letters in Applied
Microbiology 2008,47: 361–366
• Patrick D Schloss and Jo Handelsman:
Biotechnological prospects from
metagenomics., Current Opinion in
Biotechnology 2003, 14:303–310
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