Transcript Microbial Genomes - Griffith University

Microbial Genomes
• 1) Methods for Studying Microbial Genomes
• 2) Analysis and Interpretation of Whole Genome Sequences
Methods for Studying Microbial Genomes
Why study genomes?
History of genome sequencing
Methods, Principles & Approaches
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 particular
give 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 as
they 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
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 a
powerful tool in identifying new applications in for biotechnology and
new approaches to the treatment and control of pathogenic organisms
History of microbial genome sequencing
• 1977 - first complete genome to be sequenced was bacteriophage
X174 - 5386 bp
• first genome to be sequenced using random DNA fragments Bacteriophage  - 48502 bp
• 1986 - mitochondrial (187 kb) and chloroplast (121 kb) genomes of
Marchantia polymorpha sequenced
• early 90’s - 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 1990’s - many additional microbial genomes sequenced including
Archaea (Methanococcus jannaschii - 1996) and Eukaryotes
(Saccharomyces cerevisiae - 1996)
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 sequencing
projects underway
Laboratory 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 conventional
molecular biology techniques adapted to operate effectively with DNA
in a much larger size range
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 for
preparing 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
Principle of PFGE
• two factors influence DNA migration rates through conventional gels
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- charge differences between DNA fragments
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- ‘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
Principle of PFGE
Principle of PFGE
• 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 being
run 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 used
in modern laboratories are FIGE (Field Inversion Gel Electrophoresis)
and CHEF (Contour-Clamped Homogenous Electrophoresis)
CHEF
Switch Time
Electric Field 1
Electric Field 2
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Preparation of DNA for PFGE
• ideally a genomic DNA preparation that contains a high proportion of
completely or almost completely intact genome copies would be
suitable for PFGE
• conventional means of DNA preparation are unsuitable for PFGE as
mechanical 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
Preparation of DNA for PFGE
• 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 or PMSF treatment is required to remove proteinase K
activity)
• 5) plugs are loaded directly onto PFGE and run
Preparation of DNA for PFGE
• 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 less
frequency than conventional restriction enzymes such as HindIII,
BamHI etc.
• many rare cutter RE’s have 6-bp (or longer) recognition sites eg. NotI
GCGGCCGC
• 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
Large insert cloning vectors – BAC’s and
PAC’s
• 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 reliably
maintain 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 BAC’s (Bacterial Artificial Chromosomes) and PAC’s (P1derived Artificial Chromosomes)
• both BAC and PAC vectors are plasmid derived vectors distinguished
from conventional vectors by extremely tightly controlled low copy
numbers
Large insert cloning vectors – BAC’s and
PAC’s
• 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 host
genomic 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 single
copy origin of replication derived from P1 phage
• PAC vectors also contain a pUC19 cassette for improved vector
purification
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
Approaches to whole microbial genome
sequencing
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 is
therefore 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
Large
DNA
fragment
Digest and
subclone
Whole Genome
Randomly
sequence
fragments
Fill gaps
Repeat for entire genome map
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 not
sequenced)
• 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 to
generate 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
Whole Genome
Shear and
subclone
Randomly
sequence
fragments
Fill gaps
Random sequencing (shotgun) approach
• There are a number of steps in the process •
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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
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
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
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 using
software 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
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
Contig 1
Contig 2
Gap
Random Sequencing
Random Sequencing
Contig 1
FWD
Large Insert
Linking Clone
Contig 2
REV
• 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
Contig 1
Large insert
Linking Clone
Contig 2
REV
FWD
Primer Walking
Physical Gaps
• 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 of PCR products
For those contigs without
linking clones, how do you fill
the gaps?
Linking
clone
Supercontig 1
Supercontig 2
Supercontig 3
Physical Gaps
• 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 oligonucleotides
against large restriction fragments
Linked by Southern Hybridisation
PCR Product
Contig 2
FWD
Contig 6
REV
Primer Walking
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 a
3.2x 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
Example - Haemophilus influenzae
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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)
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
• Genome Databases:
– Listing of genomes: Genomes online database (GOLD)
– Comprenehsive Genome Databases : GenBank, EMBL, DDBJ, JGI,
TIGR, HAMAP, IMG, PEDANT (curation problematic, special tools
for exploring / comparing / aligning genomes)
– Taxon specific Genome Database: EcoCyc (literature derived
annotations)
Genome Annotation
The process after sequencing has been
completed.
Use of many different tools required:
Bioinformatics
Databases
Literature
Sequence
Experimental
Pipelines for the Annotation
of Genomes – Web based
Sequence
Gene prediction
Proteins
Similarity searches
against reference
databases
Calculations &
predictions (MW ,
structure, location etc)
Annotated
Proteins
Pathway prediction
Annotated Proteins
& pathways
Manual editing
Data visualization
Pipeline for genome annotation
Identifying ORF’s
• most genomes will contain genes with very little or no homology to
known genes of other organisms
• for this reason all of the possible ORF’s 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
Identifying ORF’s
• 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 identify ORF’s without using the
training procedure with only slightly reduced accuracy
• GLIMMER is a software for gene prediction and used by:
– BASYS- http://wishart.biology.ualberta.ca/basys/cgi/submit.pl
– JCVI (formerly TIGR)- http://www.tigr.org/
– SABIA- http://www.sabia.lncc.br/
Assigning function to ORF’s
• in order to assign function, all predicted ORF’s 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
ORF’s of unidentified function
• in most genome sequences many of the ORF’s identified cannot be
assigned a specific function based on homology
• although the figure varies, usually between 40 and 50% of ORF’s fall
into this category
• clearly this represents a significant gap in our knowledge of microbial
metabolism
• these ORF’s can be further divided into two categories –
• i) conserved hypothetical proteins – ORF’s with no homology to
proteins of known function but with significant homology to
unidentified ORF’s of other species
• these ORF’s are therefore functionally conserved across numerous
species and may represent important components of central
metabolism that have not yet been identified
ORF’s of unidentified function
• the more universal the distribution of these ORF’s the more likely they
have a fundamental role in metabolism
• ii) ORF’s without homologues – these are ORF’s that have no
homology to any known sequences – these may represent genes
encoding proteins related to more specific organism adaptations
• eg. Deinococcus radiodurans is a radiation resistant organism that
contains many ORF’s without homologues – many of these are thought
to be involved in specialised processes of DNA repair
O rgan ism (total
O R F ’s)
H om ologu es to
kn ow n protein s (% )
N o h om ologu es (% )
33.3
35
H om ologu es to
con served
h ypoth etical
protein s (% )
10.3
33.3
E . coli (4277)
P yrococcu s
h orikosh ii (2064)
H aem oph ilu s
in flu en zae (1709)
B . su btilis (4099)
Meth an ococcu s
jan n asch ii (1735)
58.8
18.2
23
58
38.1
5
40.6
37
21.3
56.4
31.7
ORF identification and new amino acids
In addition to the 20 amino acids, two new but rare amino acids
have now been identified:
– 21st selenocystine (Sec)
– 22nd pyrolysin (Pyl)
The Sec and Pyl containing proteins are predominantly found in
members of class δ-proteobacteria, phylum Proteobacteria.
Metagenome analysis of the uncultured δ-proteobacteria of the
gutless & mouthless worm, Olavius algarvensi, contains the
highest proportion of Sec & Pyl containing proteins to date
suggesting that symbiosis promotes Sec & Pyl genetic code
Olavius algarvensi, also contains the most wide use of the genetic
code- 63 out of the 64 possible codons
Sec:
– 99 genes, cluster into 30 protein families
– present in domains Bacteria, Archaea & Eucarya.
– Sec coded by UGA (UGA also acts as a stop codon)
ORF identification and new amino acids
Reference:
Zhang, Y. and Gladyshev, V. N. (2007). High content of
proteins containing 21st and 22nd amino acids, selenocysteine
and pyrrolysine, in a symbiotic deltaproteobacterium of gutless
worm Olavius algarvensis. Nucleic Acids Research
2007, 1–12
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 ORF’s are assigned function
• in most cases classical molecular biology tools will be necessary for
this task, however, some suggestion of function for these ORF’s would
greatly 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 (1000’s of structures!!)
• function can then be inferred on the basis of 3d structure comparisons
to 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
don’t necessarily have the same aa sequence
Microarray hybridisation
• a completely annotated microbial genome sequence, whilst a powerful
scientific tool, still doesn’t 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 gene
expression 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
Microarray hybridisation
• example – a microarray containing 97% of the predicted ORF’s 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 envelope
biosynthesis – 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
INH untreated - green
INH treated - red
Overlay
Yellow = Red + Green (no
change in expression)
Green = only expressed
without INH treatment
Red = only expressed after
INH treatment
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 these
organisms regarding specific adaptations to proliferation in remarkably
different environments?
• What conclusions can be made about evolutionary relationships
between these organisms?
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 contains
genes 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)
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
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 broad
relationships 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 morphological
characteristics 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
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’ conserved
throughout 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 most
homologous 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
A - Stable core
B - Variable shell
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 bacterium Helicobacter 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
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 the
chromosomal and plasmid sequences
• numerous systems for DNA repair, DNA damage export were
identified
• a significant proportion of the ORF’s identified had no database
matches - these may be involved in unique cellular adaptations to
radiation and stress response
Case study - Neisseria meningitits
• N. meningititis causes bacterial meningitis and is therefore an
important pathogen
• genome is 2.2 megabases in size
• 2121 ORF’s were identified with many having extremely variable
G+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 (NIME’s) - 50 to 150
bp repeat elements
• these repeat elements may be involved in enhancing recombinase
specific horizontal gene transfer
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 predicted ORF’s identified - these encode a basic set of proteins
for 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
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 of ORF’s of unknown function, in combination
with gene expression analysis and proteomics is required