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Chapter 16
Microbial
Genomics
1
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March 24, 2015
微免科 陳怡原
[email protected]
Ext. 3352
2
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Today’s lecture will discuss:
1.
2.
3.
4.
5.
What is bacterial genome?
How to determine and analyze the genome?
What is proteome?
How to determine the proteome?
What can we learn from the organization
and function of a bacterial genome?
3
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Genomics
• study of molecular organization of
genomes, their information content, and
gene products they encode
– network of interconnected circuits
– window into entire microbial communities
– evolutionary insights
4
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Determining DNA Sequences
• Sanger DNA sequencing
– most commonly used method
– referred to as the chain-termination DNA
sequencing method
– uses dideoxynucleoside triphosphates
(ddNTP)
5
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Sanger Method
Figure 16.2
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Sanger Method
• mix single strands of DNA with primer,
DNA polymerase I, 4 deoxynucleotides
(one of which is radiolabeled), small
amount of one ddNTP
• DNA synthesis occurs; random insertion
of ddNTP generates DNA fragments of
different lengths
• four reactions carried out; each with
different ddNTP
• fragments in each reaction mixture
separated electrophoretically
• gel autoradiographed and sequence read
7
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More Sanger Sequencing…
• automated sequencing
– uses four different fluorescent color dyes
instead of radiolabeled ddNTP
– electrophoresis and laser beam determines
order
8
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The Automated Sanger DNA
Sequencing
Figure 16.3
9
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Post-Sanger DNA Sequencing
• search for more rapid, less cumbersome,
and less expensive methods
• methods
– pyrosequencing
– SOLEXA sequencing
– SOLiD technology
10
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Genome Sequencing
• Whole-genome shotgun sequencing
• Single cell genome sequencing
11
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Whole-Genome Shotgun
Sequencing
• developed in 1995 by J. Craig Venter and
Hamilton Smith
• four stage process
– library construction
• generates clones of portions of genome
– random sequencing
• determines sequences of clones
– fragment alignment and gap closure
– editing
12
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Whole-Genome
Shotgun Sequencing
Figure 16.6
13
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Single-Cell Genomic
Sequencing
• femtograms of DNA from a single cell are
amplified to micrograms of DNA needed
for sequencing
• multiple strand displacement (MSD)
– amplification of 70–75% of genome
amplified
– combining cells reduces mistakes
14
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Single-Cell Genomic Sequencing
Figure
16.7
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Bioinformatics
• analysis of genome data using computers
• generates data on genome content,
structure, and arrangement
• also provides data on protein structure
and function
• uses annotation to determine location of
genes on newly sequenced genome
• further examination carried out using in
silico analysis
16
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Genome Annotation - 1
• process that locates genes in the genome
map
• identifies each open reading frame in
genome
– a reading frame >100 codons that is not
interrupted by a stop codon
– there is an apparent ribosomal binding site
at the 5’ end and terminator sequences at
the 3’ end
17
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Finding Potential Protein
Coding Genes
Figure 16.8
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Bioinformatics - 2
• ORFs are presumed to encode protein
(coding sequences, CDS)
• BLAST (basic local alignment search tool)
computer program
– base by base comparison of two or more
gene sequences
– assign tentative function of gene or protein
structure
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Analysis of Conserved Regions
Figure 16.9
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Functional Genomics
• determination of how genome works
• uses physical maps of location of genes
• provides information on
– metabolic pathways
– transport mechanisms
– regulatory and signal transduction
mechanisms
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Physical Map of the
Haemophilus influenza Genome
Figure
16.10
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Metabolic Pathways and Transport
systems of Treponema pallidum
Figure 16.11
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DNA Microarray Analysis
• can determine which genes are expressed
at a specific time
• arrays are solid supports to which DNA is
attached
• each DNA spot (called a probe),
represents a single gene or ORF
• commercially prepared microarrays can
be purchased
24
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Gene Microarrays
• spotted arrays
– prepared by robotic application of DNA
probe
• examples of probes = PCR product, cDNA or
oligonucleotide)
• oligonucleotide probes from eukaryotes are
called expressed sequence tags (EST)
25
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Analysis of Gene Expression
Using Microarrays
• based on hybridization between the probe
DNA and the targets (the nucleic acids to be
analyzed)
– targets are labeled with fluorescent dyes and
then incubated with the gene chip
– unbound target is washed off
– the chip is scanned with laser beams to
detect fluorescence which indicates that
hybridization has occurred
26
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A Microarray System
Figure 16.12
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Applications of Microarray
Analysis
• which genes have changed expression in
response to environmental changes
– hierarchical cluster analysis
• groups genes with similar function or patterns of
regulation
– analysis of transcriptome - all the mRNA
present after environmental challenge
28
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Hierarchical
Cluster
Analysis of
Gene
Expression
Figure 16.13
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Proteomics
• the study of the proteome
– the entire collection of proteins that an
organism produces
• provides information about genome
function not available from mRNA studies
• information determines what is actually
happening in cells is referred to as
functional proteomics
30
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Analysis of
Proteome
• proteome often analyzed
by two-dimensional gel
electrophoresis
– first dimension
• isoelectric focusing – pH
gradient determines
isoelectric point
– second dimension
• electrophoresis (SDSPAGE) and separation
by molecular weight
Figure
16.14
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Further Proteome Analysis
• Tandem Mass Spectrometry
– unknown spot from 2-D gel is cut and
cleaved
– fragments are analyzed by mass
spectrometer
– mass of fragments is plotted
– protein tentatively identified from
probable amino acid composition
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Mass
Spectrometry
Figure 16.15
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Structural Proteomics
• protein modeling
– determination of 3-D structure of proteins
– predicting structure of other proteins and
proteins complexes
• lipidomics, glycomics
– cell’s lipid and carbohydrate profile
• metabolomics
– small molecule metabolites
34
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Probing DNA-Protein Interactions
• chromatin immunoprecipitation (ChIP)
– allows for study of interactions in absence
of purified protein
– proteins are stably attached to DNA
– protein specific antibodies are cross-linked
– fluorescently labeled DNA is hybridized to
microarray for identification
35
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ChIP-Chip
Analysis
Figure 16.16
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Systems Biology
• integration of “parts lists” of cells with
molecular interactions that become
pathways for catabolism, anabolism,
regulation, behavior, environmental
responses, etc.
– holistic study of cells
– may be important in studying host microbe
interactions
37
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Comparative Genomics - 1
• set of analyses by which gene function and
evolution can be inferred by studying
similar nucleotide and amino acid
sequences found among organisms
• comparisons within domains
38
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Microbial Genome Sizes
Figure 16.17
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Comparative Genomics - 2
• comparisons of genomes of strains within
species and among species
– core genome
• set of genes found in all members of a
monophyletic group
• represent minimal number of genes needed
– pan-genome
• combination of all genes of all strains
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Core and Pan-Genomes
Figure 16.18
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Comparative Genomics - 3
• horizontal gene transfer (HGT)
• genomic islands (permanently integrated
mobile genetic elements)
• pathogenicity islands (virulence proteins)
• phylogenic relationships between
microbes can be studied by synteny –
order of genes on genome
42
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Synteny
Figure 16.19
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Comparative Genomics - 4
• pathogen virulence genes
– pseudogenes – non-functional genes in
non-pathogen relatives
• reverse vaccinology
– development of new vaccines using only
specific proteins of pathogens
44
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Comparative Genomic Analysis
between two Mycobacterium species
Figure 16.20
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Metagenomics
• environmental genomics
– cultivation-independent technique
– used to learn more about the diversity and
metabolic potential of microbial
communities
– takes a census of microbial populations and
can determine the presence and level of
classes of genes
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From the environment……
Figure 16.21
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Phylotypes
• genes that indicate taxonomy may aid in
metabolic activities of microbial
communities
• examples
– finding rhodopsin-like genes in marine
microbes is an exciting discovery that
requires a reassessment of oceanic carbon
cycles
– prokaryotic biodiversity of Segrasso sea
– microbiome in humans and normal
microbiota
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Phylogenetic Diversity of
Sargasso Sea Microbes
Figure 16.22
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Summary
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Genome sequencing
Bioinformatics
Functional genomics
Proteomics
System biology
Comparative genomics
Metagenomics
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