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Microbial Genomes
1) Methods for Studying Microbial Genomes
2) Analysis and Interpretation of Whole Genome Sequences
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Why study microbial genomes?
until whole genome analysis became viable, life sciences have been
based on a reductionist principle dissecting cell and systems into
fundamental components for further study
studies on whole genomes and whole genome sequences in particulargive us a complete genomic blueprint for an organism
we can now begin to examine how all of these parts operate
cooperatively to influence the activities and behavior of an entire
organism a complete understanding of the biology of an organism
microbes provide an excellent starting point for studies of this type asthey have a relatively simple genomic structure compared to higher,
multicellular organisms
studies on microbial genomes may provide crucial starting points for
the understanding of the genomics of higher organisms
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Why study microbial genomes?
analysis of whole microbial genomes also provides insight into
microbial evolution and diversity beyond single protein or gene
phylogenies
in practical terms analysis of whole microbial genomes is also apowerful tool in identifying new applications in for biotechnology and
new approaches to the treatment and control of pathogenic organisms
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H
istory of microbial genome sequencing
1977 - first complete genome to be sequenced was bacteriophage
JX174 - 5386 bp
first genome to be sequenced using random DNA fragments -
Bacteriophage P - 48502 bp
1986 - mitochondrial (187 kb) and chloroplast (121 kb) genomes of
Marchantia polymorpha sequenced
early 90s - cytomegalovirus (229 kb) and Vaccinia (192 kb) genomes
sequenced
1995 - first complete genome sequence from a free living organism -
Haemophilus influenzae (1.83 Mb)
late 1990s - many additional microbial genomes sequenced including
Archaea (Methanococcus jannaschii - 1996) and Eukaryotes
(Saccharomyces cerevisiae - 1996)
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Microbial genomes sequenced to date
currently there are 32 complete, published microbial genomes 25
domain Bacteria, 5 Domain Archaea, 1 domain Eukarya
(www.tigr.org)
around 130 additional microbial genome and chromosome sequencingprojects underway
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L
aboratory tools for studying whole genomes
conventional techniques for analysing DNA are designed for the
analysis of small regions of whole genomes such as individual genes or
operons
many of the techniques used to study whole genomes are conventionalmolecular biology techniques adapted to operate effectively with DNA
in a much larger size range
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Pulsed Field Gel Electrophoresis
agarose gel electrophoresis is a fundamental technique in molecular
biology but is generally unable to resolve fragments greater than 20
kilobases in size (whole microbial genomes are usually greater than
1000 kilobases in size) PFGE (pulsed field gel electrophoresis) is a adaptation of conventional
agarose gel electrophoresis that allows extremely large DNA
fragments to be resolved (up to megabase size fragments)
essential technique for estimating the sizes of whole
genomes/chromosomes prior to sequencing and is necessary forpreparing large DNA fragments for large insert DNA cloning and
analysis of subsequent clones
also a commonly used and extremely powerful tool for genotyping and
epidemiology studies for pathogenic microorganisms
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Principle ofPFGE
two factors influence DNA migration rates through conventional gels
- charge differences between DNA fragments
- molecular sieve effect of DNA pores
DNA fragments normally travel through agarose pores as spherical
coils, fragments greater than 20 kb in size form extended coils and
therefore are not subjected to the molecular sieve effect
the charge effect is countered by the proportionally increased friction
applied to the molecules and therefore fragments greater than 20 kb do
not resolve
PFGE works by periodically altering the electric field orientation
the large extended coil DNA fragments are forced to change
orientation and size dependent separation is re-established because the
time taken for the DNA to reorient is size dependent
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Principle ofPFGE
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Principle ofPFGE
the most important factor in PFGE resolution is switching time, longer
switching times generally lead to increased size of DNA fragments
which can be resolved
switching times are optimised for the expected size of the DNA beingrun on the PFGE gel
switch time ramping increases the region of the gel in which DNA
separation is linear with respect to size
a number of different apparatus have been developed in order to
generate this switching in electric fields however most commonly usedin modern laboratories are FIGE (Field Inversion Gel Electrophoresis)
and CHEF (Contour-Clamped Homogenous Electrophoresis)
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+
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+
+ +
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+
-
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Electric Field 1 Electric Field 2
Switch Time
CHEF
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Preparation of DNA forPFGE
ideally a genomic DNA preparation that contains a high proportion of
completely or almost completely intact genome copies would be
suitable forPFGE
conventional means of DNA preparation are unsuitable forPFGE asmechanical shearing and low-level nuclease activity will result in
fragmented DNA with an average size much smaller than an entire
microbial genome (usually less than 200 kb in size)
the solution to this is to prepare genomic DNA from whole cells in a
semisolid matrix (ie. agarose) that eliminates mechanical shearing a very high concentration of EDTA is also used at all times in order to
eliminate all nuclease activity
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Preparation of DNA forPFGE
Procedure
1) intact cells are mixed with molten LMT agarose and set in a mold
forming agarose plugs
2) enzymes and detergents diffuse into the plugs and lyse cells
3) proteinase K diffuses into plugs and digests proteins
4) if necessary restriction digests are performed in plugs (extensive
washing orPMSF treatment is required to remove proteinase K
activity)
5) plugs are loaded directly onto PFGE and run
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Preparation of DNA forPFGE
for restriction digests, conventional enzymes are unsuitable as they cut
frequently on an entire genome sequence producing DNA fragments
that are far too small
rare cutter restriction endonucleases cut genomic DNA with far lessfrequency than conventional restriction enzymes such as HindIII,
BamHI etc.
many rare cutter REs have 6-bp (or longer) recognition sites eg. NotI
GCGGCCGC
in many cases the frequency of cutting is highly species dependent eg.BamHI will cut far less frequently on a low GC% genome when
compared to a intermediate or high GC content genome
suitable rare cutter enzymes therefore have to be determined
experimentally for each new species being studied
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Large insert cloning vectors BACs and
PACs
DNA cloning is another technique fundamental to molecular biology
that requires adaptation in order to be useful in studying DNA at a
whole genome scale
conventional plasmid derived cloning vectors are only able to reliablymaintain inserts less than 20 kb in size
there are a number of approaches to generating clones with inserts in
an intermediate size range (20 80 kB) such as cosmids, etc.
the most commonly used vectors for cloning extremely large DNA
inserts are BACs (Bacterial Artificial Chromosomes) and PACs (P1-derived Artificial Chromosomes)
both BAC and PAC vectors are plasmid derived vectors distinguished
from conventional vectors by extremely tightly controlled low copy
numbers
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Large insert cloning vectors BACs and
PACs
these very low copy numbers help to limit the strain on host cellular
resources generated by very large DNA inserts thus eliminating the
rejection of large insert clones
low copy numbers also help to limit recombination events with hostgenomic DNA
BAC and PAC vectors both utilise E. coli as the host organism
BAC vectors are based on the E. coli single copy F-factor plasmid
the F-factor origin of replication is very tightly controlled
PAC vectors are based on an identical principle but instead use a singlecopy origin of replication derived from P1 phage
PAC vectors also contain a pUC19 cassette for improved vector
purification
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Approaches to whole microbial genome
sequencing
aim of microbial genome sequencing projects is to construct, from 500
800 bp sequencing reads containing about 1% mistakes, a genome
sequence of several megabases with an error rate lower than 1 per
10000 nucleotides with improving software, decreasing computation costs and
advancements in automated DNA sequencing, an entire microbial
genome project can be completed in a small laboratory in 1-2 years
there are two main approaches to sequencing microbial genomes the
ordered clone approach and direct shotgun sequencing both require both large and small insert genomic DNA libraries in
order to be effective
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Approaches to whole microbial genome
sequencing
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Ordered Clone Approach
essentially this technique involves constructing a map of overlapping
large insert clones covering the whole genome and then completely
sequencing the minimum subset of these ordered clones
there are a number of methods used to order clones including
restriction fingerprinting and hybridisation mapping
once an ordered large insert clone set is identified, a whole genome
sequence is determined by either shotgun or partial primer walk
sequencing of each insert
the ordered clone approach to DNA sequencing requires a large
amount of characterisation prior to actual DNA sequencing and istherefore a relatively time consuming approach, however, it may be
cheaper than shotgun sequencing an entire genome as less redundant
sequencing is required
with rapid decreases in costs for computing power and sequencing this
method is no longer considered viable for small (< 5 Mb) genomes
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Whole Genome
Large
DNA
fragmentDigest and
subclone
Randomly
sequence
fragments
Fill gaps
Repeat for entire genome map
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Random sequencing (shotgun) approach
this is the currently the most commonly used strategy for microbial
whole genome sequencing
sequences from both ends of a large number of small and large insert
clones are generated and overlapping sequences joined together to
form a contig of the whole genome sequence (whole inserts notsequenced)
although this requires enormous amounts of DNA sequencing (often
up to 10x genome coverage) and computational power for sequence
assembly, it is a relatively rapid approach to whole genome sequencing
the first 90 95% of the genome sequence is relatively easy togenerate by shotgun sequencing resulting in several hundred discrete
contigs
filling the gaps to produce a single contig is the most difficult and time
consuming phase of this process
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Whole Genome
Shear and
subclone
Randomly
sequence
fragments
Fill gaps
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Random sequencing (shotgun) approach
There are a number of steps in the process -
1) Random large and small insert library construction
2) High throughput DNA sequencing
3) Sequence assembly
4) Ordering of contigs
5) Primer walking to complete sequence
6) Annotation
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Library construction
Both conventional and large insert genomic DNA libraries should be
constructed
the small insert library will be used for the bulk of the sequencing in
order to generate suitable coverage of the complete genome
the large insert library (BAC, PAC, cosmid etc.) will be used as a
scaffold during the sequence closure phase
it is crucial to ensure that both libraries are as random as possible -
mechanical shearing is often used to generate small DNA fragments
it is also important that each clone contains only one DNA fragment
and as such specialised methods for library construction must be used
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DNA Sequencing
DNA sequences are generated using vector primers for both ends of
inserts
at least 6X coverage of the genome is required although 9 to 10X
coverage is often generated
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Sequence assembly and gap closure
4 major steps in sequence assembly and gap closure -
1) random sequences initially interpreted using highly accurate base
calling software and assembled to generate primary contigs usingsoftware such as PHRAPP
2) computational and experimental techniques used to identify linking
clones and order primary contigs
3) primer walk sequencing of linking clones and PCR products to fill
sequence gaps between contigs 4) confirmation of contig order by PCR
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Linking Clones
one of the most effective means of contig ordering and gap filling is
linking clones
linking clones are those whose terminal sequences (from either end of
the insert) belong to different contigs if the orientation of the sequences and the distance to the end of the
contig are compatible with with the size of the insert, the two contigs
are likely to be linked
the larger the insert the more likely a clone will be a linking clone
this is why random sequencing is also performed on large insert clones- they are far more likely to form linking clones
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Contig 1 Contig 2
Random Sequencing Random Sequencing
Gap
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Contig 1 Contig 2
FWD REV
Large Insert
Linking Clone
Once all possible linking clones are identified -
gaps are classified into two categories - those with linking clones
(template available for sequencing) and physical gaps without linking
clones ( no DNA template for the region)
for those gaps with suitable linking clones, the gaps confirmed by
PCR and closed by primer walk sequencing
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Contig 1 Contig 2
FWD REV
Large insert
Linking Clone
Primer Walking
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Contigs separated with physical gaps (no linking clones) are usually
spanned by PCR on genomic DNA using primers from each end of the
contigs
the PCR products can then be sequenced to close the gaps
without linking clones other techniques to order contigs must be used
in order to guide the selection ofPCR products
Physical Gaps
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Supercontig 1
Supercontig 2
Supercontig 3
Linking
clone
For those contigs without
linking clones, how do you fill
the gaps?
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contigs can be ordered by -
peptide linking - contig ends having regions with homology to the
same gene (or operon / gene cluster)
southern hybridisation of labelled contig terminal oligonucleotidesagainst large restriction fragments
Physical Gaps
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Contig 2 Contig 6
FWD REV
Primer Walking
PCRProduct
Linked by Southern Hybridisation
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Gapped Microbial Genomes
considering the cost and difficulty in filling gaps between contigs some
interest has been generated by the analysis of gapped microbial
genomes
each gap is usually very small on average (approximately 75 bp for a3.2x coverage library)
increasing bioinformatic resources available mean that these gaps have
little influence on functional reconstruction
eg. Thiobacillus ferroxidans - all assigned amino acid biosynthesis
genes (140 in total) identified from a gapped genome of 1912 contigs error rates tend to be relatively high compared to genome sequences
with greater coverage
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Example -Haemophilus influenzae
first complete genome sequence of a free living organism (1995)
important pathogen
genome is around 1.83 megabases in size
random sequencing was done for both small insert and large insert
(lambda) libraries
sequencing reactions performed by eight individuals using fourteen
ABI 377 DNA sequencers per day over a three month period
in total around 33000 sequencing reactions were performed on 20000
templates
plasmid extraction performed in a 96 well format
11 mb of sequence was intially used to generate 140 contigs
gaps were closed by lambda linking clones (23), peptide links (2),
Southern analysis (37) and PCR (42)
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Annotation of Genome Sequences
a microbial genome sequence alone is only raw data it needs to be
interpreted in order to be of any scientific significance
the process of predicting the location and function of all possible
coding sequences (genes) in a genome sequence is known as
annotation
although an annotated genome sequence provides a large amount of
important information it is still merely a starting point for completely
characterising an organism
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Identifying ORFs
most genomes will contain genes with very little or no homology to
known genes of other organisms
for this reason all of the possibleORFs need to be identified without
relying totally on homology most efficient means for identifying potential genes in genome
sequences is a three step process
1) submit entire sequence as a 6-frame translation for BLAST analysis
in order to identify some protein coding regions on the basis of high
levels of homology 2) use these initial coding regions to determine the sequence
characteristics (GC content, codon bias etc.) that distinguish coding
and non-coding regions of the genome (training the software)
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Identifying ORFs
3) reanalyse the genome sequence using this data (plus potential
ribosome binding sequences) in order to identify all the potential genes
using this process it has been experimentally shown that around 94%
of genes can be accurately predicted algorithms are also available to identifyORFs without using the
training procedure with only slightly reduced accuracy
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Assigning function to ORFs
in order to assign function, all predicted ORFs are translated to amino
acid sequence and analysed by homology searches against sequence
databases (usually Genbank)
for each ORF there are three possible results - i) clear sequence homology indicating function
ii) blocks of homology to defined functional motifs
- these should be confirmed experimentally
iii) no significant homology or homology to proteins of unknown
function
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ORFs of unidentified function
in most genome sequences many of theORFs identified cannot be
assigned a specific function based on homology
although the figure varies, usually between 40 and 50% ofORFs fall
into this category clearly this represents a significant gap in our knowledge of microbial
metabolism
these ORFs can be further divided into two categories
i) conserved hypothetical proteins ORFs with no homology to
proteins of known function but with significant homology tounidentified ORFs of other species
these ORFs are therefore functionally conserved across numerous
species and may represent important components of central
metabolism that have not yet been identified
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ORFs of unidentified function
the more universal the distribution of theseORFs the more likely they
have a fundamental role in metabolism
ii) ORFs without homologues these are ORFs that have no
homology to any known sequences these may represent genesencoding proteins related to more specific organism adaptations
eg. Deinococcus radiodurans is a radiation resistant organism that
contains many ORFs without homologues many of these are thought
to be involved in specialised processes of DNA repair
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Organism (total
ORFs)
Homologues to
known proteins (%)
Homologues to
conserved
hypothetical
proteins (%)
No homologues (%)
E. coli (4277) 33.3 10.3 56.4
Pyrococcus
horikoshii (2064)
35 33.3 31.7
Haemophilus
influenzae (1709)
58.8 18.2 23
B. subtilis (4099) 58 5 37
Methanococcus
jannaschii (1735)
38.1 40.6 21.3
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Structural genomics
in order to gain a complete understanding of an organism and fully
exploit the potential offered by microbial genome sequencing, it is
essential that these unidentified ORFs are assigned function
in most cases classical molecular biology tools will be necessary for
this task, however, some suggestion of function for theseO
RFs wouldgreatly improve the efficiency of this process
one possibility is structural genomics
this is the process of determining three dimensional structures of all the
gene products encoded in a microbial genome (1000s of structures!!)
function can then be inferred on the basis of 3d structure comparisonsto other proteins
this relies on the principle that structure determines functions and
although two proteins with similar amino acid sequences can be
assumed to have similar structures, two proteins with similar structure
dont necessarily have the same aa sequence
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Microarray hybridisation
a completely annotated microbial genome sequence, whilst a powerful
scientific tool, still doesnt provide all of the information needed to
understand the complete biology of an organism as it essentially a
static picture of the genome
for truly complete characterisation, the dynamic nature of geneexpression within a microbial cell needs to be determined
microarray technology allows whole organism gene expression to be
investigated
PCR products of every gene from a complete genome sequence are
bound in a high density array on a glass slide these arrays are probed with fluorescently labelled cDNA prepared
from whole RNA under specific environmental conditions
the level of cDNA for each ORF is then quantified using high
resolution image scanners
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Microarray hybridisation
example a microarray containing 97% of the predictedORFs from
Mycobacterium tuberculosis was used to investigate the response to
the antituberculosis drug isoniazid (INH)
INH was found to induce several genes related to outer lipid envelopebiosynthesis consistent with the drugs physiological mode of action
a number of additional genes were also induced which may provide
potential drug targets in the future
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INH untreated - green
INH treated - red
Yellow = Red + Green (no
change in expression)
Green = only expressed
without INH treatment
Red = only expressed after
INH treatment
Overlay
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Characteristics of sequenced genomes
the 32 complete genome sequences currently available cover a diverse
range in terms of phylogeny and environments (eg. human pathogens,
plant pathogens, extremophiles etc.)
what conclusions can be made by comparing the genomes of theseorganisms regarding specific adaptations to proliferation in remarkably
different environments?
What conclusions can be made about evolutionary relationships
between these organisms?
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Horizontal gene transfer
before microbial genome sequences became available most of the
focus of microbial evolution was on vertical transmission of genetic
information mutation recombination and rearrangement within the
clonal lineage of a single microbial population genome sequences have demonstrated that horizontal transfer of genes
(between different types of organisms) are widespread and may occur
between phylogentically diverse organisms
generally speaking, essential genes (such as 16S rRNA) are unlikely to
be transferred because the potential host most likely already containsgenes of this type that have co-evolved with the rest of its cellular
machinery and and cannot be displaced
genes encoding non-essential cellular processes of potential benefit to
other organisms are far more likely to be transferred (eg. those
involved in catabolic processes)
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Horizontal gene transfer
clearly, lateral transfer of genomic information has enormous potential
in improving an microorganisms ability to compete effectively - this
may explain why horizontally transferred genes appear so frequently
and ubiquitously in microbial genomes an example of this is horizontally transferred genes between Archaeal
and Bacterial hyperthermophiles -
Thermotoga maritima has 15 clusters of genes (4-20kb) most similar to
equivalent Archaeal hyperthermophile gene regions
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Whole genome phylogenetic analysis
most of the evolutionary relationships between microorganisms are
inferred by comparison of single genes usually 16s rRNA genes
although extremely effective, single gene phylogenetic trees only
provide limited information which can make determining broadrelationships between major groups difficult
phylogenetic relationships can be determined by whole genome
comparisons of the observed absence or presence of protein encoding
gene families
in effect this is similar to using the distribution of morphologicalcharacteristics to determine phylogeny without the problem of
convergent evolution
trees produced using this method are similar to 16s rRNA trees,
however, as more genome sequences become available more detailed
conclusions can be drawn using this method
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Archaeal Genomes
analysis of the 5 complete genome available for members of the
domain Archaea has provided new insights into relationships between
Archaea, Bacteria and Eukaryotes
around 35% of the Archaeal genes form a stable core conservedthroughout the domain
most of these encode proteins involved in transcription, translation and
DNA metabolism and some central metabolic pathways
the remainder of the genome is classified as a variable shell
a relatively high proportion of the variable shell genes are mosthomologous to their bacterial counterparts - this suggests horizontal
gene transfer events
a relatively high proportion of the stable core genes are most similar to
Eukaryotic genes
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A - Stable core B - Variable shell
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Species and strain specific genetic diversity
although genome sequencing and analysis is very useful when
comparing phylogenetically distant taxa, it is also of interest to
examine the genomes of very closely related microorganisms
this allows a more quantitative approach for examining the
relationships between genotype and phenotype
complete genome sequences have been determined for two species of
the genus Chlamydia (pneumoniae and trachomatis)
although the overall genome structure was quite similar, C.pneumoniae
contained an additional 214 genes most of which have an unknown
function two strains of the bacteriumHelicobacter pylori have been completely
sequenced (26695 and J99)
overall the two strains were very similar genetically with only 6% of
genes being specific to each strain
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Case study - Deinococcus radiodurans
D. radiodurans R1 is an extremely radiation resistant bacterium
genome (total of 3.3 megabases) consists of two chromosomes (2.6
and 0.4 mb) a megaplasmid (177 kb) and a small plasmid (44 kb)
considerable genetic redundancy was observed in both thechromosomal and plasmid sequences
numerous systems for DNA repair, DNA damage export were
identified
a significant proportion of theORFs identified had no database
matches - these may be involved in unique cellular adaptations to
radiation and stress response
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Case study - Neisseria meningitits
N. meningititis causes bacterial meningitis and is therefore an
important pathogen
genome is 2.2 megabases in size
2121O
RFs were identified with many having extremely variableG+C% (recently acquired genes)
many of these recently acquired genes are identified as cell surface
proteins
there is a remarkable abundance and diversity of repetitive DNA
sequences
nearly 700 neisserial intergenic mosaic elements (NIMEs) - 50 to 150
bp repeat elements
these repeat elements may be involved in enhancing recombinase
specific horizontal gene transfer
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Case study - Borellia burgdorferi
B. burgdorferi is a spirochaete which causes Lyme disease
it has a 0.91 megabase linear genome and at least 17 linear and circular
plasmids which total 0.53 megabases
853 predictedO
RFs identified - these encode a basic set of proteinsfor DNA replication, transcription, translation and energy metabolism
no genes encoding proteins involved in cellular biosynthetic reactions
were identified - appears to have evolved via gene loss from a more
metabolically competent precursor
there is significant amount of genetic redundancy in the plasmid
sequences although a biological role has not been determined
it is possible the these plasmids undergo frequent homologous
recombination in order to generate antigenic variation in surface
proteins
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Summary
Microbial genome sequencing and analysis is a rapidly expanding and
increasingly important strand of microbiology
important information about the specific adaptations and evolution of
an organism can be determined from genome sequencing
however, genome sequencing merely a strong starting point on road to
completely understanding the biology of microorganisms
further characterisation ofORFs of unknown function, in combination
with gene expression analysis and proteomics is required
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