Transcript Bacterial Genome Structure, Replication and Gene regulation

Genomics and other “omics”
• Genome sequencing - individual organism
(genomics), community of organisms
(metagenomics)
• Searching the databases
• Transcriptional analysis (transcriptomics)
• Proteomics
• Metabolomics (detect small metabolites)
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Genomic analysis: Step 1. Predicting open
reading frames (orfs) by computer algorithms
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Genomic analysis: Step 1 (cont.). Predicting
open reading frames by computer algorithms
• Advantages
– Gives a readout of large open reading frames
• Limitations
– Some genes have start codons that are not ATG
– Ignores very small open reading frames. May
miss hormone-like peptides, small regulatory
peptides, quorum sensing peptides.
– Does not detect small regulatory RNAs.
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Genomic analysis: Step 2. Database
searches
• DNA sequence alignments
– Best for finding nearly identical genes
– Find sequence motifs (e.g., helix-turn-helix in DNA binding
proteins)
• Linear amino acid sequence alignments
– Best for finding homologs that may be more distantly
related
– Annotation can be ambiguous
• Example: Elongation factors and tetracycline resistance genes
(ribosomal protection type)
• Example: Enzymes that are not present in an organism
• Annotations are hypotheses!!!
• Structural predictions – structural homologs
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BLASTP 2.2.6 [Apr-09-2003]
SusA-8-03
Query=
(565 letters)
Database: Completed Bacteroides thetaiotaomicron VPI-5482;
1,480,858 sequences; 476,119,222 total letters
Distribution of 26 Blast Hits on the Query Sequence
Sequences producing significant alignments:
gi|29349112|ref|NP_812615.1|
gi|29349106|ref|NP_812609.1|
gi|29350098|ref|NP_813601.1|
gi|29347073|ref|NP_810576.1|
gi|29350097|ref|NP_813600.1|
gi|29346181|ref|NP_809684.1|
gi|29346183|ref|NP_809686.1|
gi|29346689|ref|NP_810192.1|
gi|29347520|ref|NP_811023.1|
gi|29345677|ref|NP_809180.1|
gi|29346515|ref|NP_810018.1|
gi|29347070|ref|NP_810573.1|
gi|29348342|ref|NP_811845.1|
gi|29349419|ref|NP_812922.1|
gi|29348421|ref|NP_811924.1|
gi|29346850|ref|NP_810353.1|
gi|29345906|ref|NP_809409.1|
gi|29347285|ref|NP_810788.1|
Score
E
(bits) Value
alpha-amylase (neopullulanase)...
alpha-amylase, susG [Bacteroid...
alpha-amylase precursor [Bacte...
pullulanase precursor [Bactero...
pullulanase precursor [Bactero...
1,4-alpha-glucan branching enz...
alpha-amylase 3 [Bacteroides t...
putative anti-sigma factor [Ba...
hypothetical protein [Bacteroi...
two-component system sensor hi...
phosphoglycerate mutase 1 [Bac...
phosphoglycerate mutase [Bacte...
Methionyl-tRNA synthetase [Bac...
DNA-methyltransferase [Bactero...
putative outer membrane protei...
putative outer membrane protei...
TonB-dependent receptor [Bacte...
putative outer membrane protei...
1076
79
67
61
59
45
38
35
33
30
29
29
28
28
28
28
27
27
0.0
1e-15
6e-12
2e-10
2e-09
1e-05
0.002
0.019
0.094
0.47
1.0
1.0
2.3
2.3
2.3
3.0
4.0
5.2
5
Protein Structure Prediction
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“Transcriptomics” – Measuring gene
expression directly (mRNA)
• Types of analysis
– Microarray – measures expression of many genes at a time
– RT-PCR – measures expression of one gene at a time
• Advantages
– Microarrays, like transposon mutagenesis, find previously
unsuspected genes of interest
– Not necessary to make fusions to every gene
• Disadvantages (compared to fusions)
– Microarray data needs to be checked by RT-PCR
– Fusions can be made to monitor translation
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Microarray - Measuring Gene Expression
of Many Genes at a Time
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New variations of the microarray
approach
• Make a few labeled DNA copies of each
mRNA using RT-PCR – increases
sensitivity
• DNA copies of mRNA from cells grown
under different conditions labeled with
different fluorophores (e.g. red for low
iron, green for high iron), then mixture
is placed on a single slide
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Uses of microarrays
• Compare gene expression under different
conditions
• Determine effects of mutations, eg, in
regulatory proteins – effect may be more
complex than you thought!
• Effects of overexpression of certain genes –
less commonly done
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Metagenomics – genome sequencing of
entire bacterial populations
• Sample contains bacterial population (e.g. water
sample, human colon contents)
• Total DNA extracted, non-DNA impurities removed
• High throughput sequencing (e.g. 454 sequencing)
• Limitations
– Assembly
– Interpretation!!
• Transcriptome
– RT-PCR amplifies messages as DNA, sequence DNA
– Limitation: lots of rRNA, random priming of RT-PCR
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Proteomics
• Detects proteins produced under different conditions
• Two dimensional gel creates an array of protein spots
– First dimension: isoelectric focusing (pH gradient)
– Second dimension: SDS denaturing gel
• Proteins extracted individually, fragmented by proteases, run
through a mass spectrometer – matched with fragments
predicted from DNA sequence.
• Advantages
– Detect proteins not RNA (post transcsriptional regulation
• Limitations
–
–
–
–
Only the most highly expressed proteins are detected
Overlapping spots may be difficult to resolve
Need to go through the MS step
Not likely to be useful in metagenomics
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Conclusions
(according to AAS)
• Availability of new technologies is forcing a
shift from single gene-single pathway
thinking to a more global way of thinking.
• Increased need to focus on a specific
biological question
• Most technologies now provided by
centralized services – technology itself is
uninteresting, only interesting thing is what
you can do with it!!
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