Microbial Genomes

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Microbial Genomes

• 1) Methods for Studying Microbial Genomes
• 2) Analysis and Interpretation of Whole Genome
  Sequences

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• Methods for Studying Microbial Genomes

Why study genomes? History of genome
sequencing Methods, Principles Approaches
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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 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

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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 a powerful tool in identifying
  new applications in for biotechnology and new
  approaches to the treatment and control of
  pathogenic organisms

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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 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 sequencing projects underway

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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

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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 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

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Principle of PFGE

• 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 of PFGE
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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)

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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

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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

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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 REs 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

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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 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 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 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

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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 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 (lt 5 Mb) genomes

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Large DNA fragment
Digest and subclone
Whole Genome
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 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

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Shear and subclone
Whole Genome
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 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

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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
Gap
Random Sequencing
Random Sequencing
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Large Insert Linking Clone
Contig 1
Contig 2
REV
FWD

• 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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Large insert Linking Clone
Contig 1
Contig 2
REV
FWD
Primer Walking
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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

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For those contigs without linking clones, how do
you fill the gaps?
Linking clone
Supercontig 1
Supercontig 2
Supercontig 3
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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

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Linked by Southern Hybridisation
Contig 2
Contig 6
PCR Product
FWD
REV
Primer Walking
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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 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

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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
• 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)

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Genome Annotation

• The process after sequencing has been completed.
  
• Use of many different tools required
• Bioinformatics
• Databases
• Literature
• Sequence
• Experimental

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Pipelines for the Annotation of Genomes Web
based
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Pipeline for genome annotation
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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 possible ORFs 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 identify ORFs
  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/cg
  i/submit.pl
• JCVI (formerly TIGR)- http//www.tigr.org/
• SABIA- http//www.sabia.lncc.br/

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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 the ORFs
  identified cannot be assigned a specific function
  based on homology
• although the figure varies, usually between 40
  and 50 of ORFs 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 to unidentified 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 these
  ORFs 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 genes encoding 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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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
  d-proteobacteria, phylum Proteobacteria.
• Metagenome analysis of the uncultured
  d-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)

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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, 112

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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 these ORFs 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 (1000s 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 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 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

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Microarray hybridisation

• example a microarray containing 97 of the
  predicted ORFs 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

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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
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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 these organisms 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 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)

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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 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

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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 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

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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 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

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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 the chromosomal and plasmid sequences
• numerous systems for DNA repair, DNA damage
  export were identified
• a significant proportion of the ORFs 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
• 2121 ORFs were identified with many having
  extremely variable GC (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 predicted ORFs 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

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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 of ORFs of unknown
  function, in combination with gene expression
  analysis and proteomics is required