Genomics and other “omics”

1. Genomics and other “omics” • Genome sequencing - individual organism (genomics), community of organisms (metagenomics) • Searching the databases • Transcriptional analysis (transcriptomics) • Proteomics • Metabolomics (detect small metabolites)

2. Genomic analysis: Step 1. Predicting open reading frames (orfs) by computer algorithms

3. 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.

4. 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

5. 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 Score E Sequences producing significant alignments:(bits) Value gi|29349112|ref|NP_812615.1| alpha-amylase (neopullulanase)... 1076 0.0 gi|29349106|ref|NP_812609.1| alpha-amylase, susG [Bacteroid... 79 1e-15 gi|29350098|ref|NP_813601.1| alpha-amylase precursor [Bacte... 67 6e-12 gi|29347073|ref|NP_810576.1| pullulanase precursor [Bactero... 61 2e-10 gi|29350097|ref|NP_813600.1| pullulanase precursor [Bactero... 59 2e-09 gi|29346181|ref|NP_809684.1| 1,4-alpha-glucan branching enz... 45 1e-05 gi|29346183|ref|NP_809686.1| alpha-amylase 3 [Bacteroides t... 38 0.002 gi|29346689|ref|NP_810192.1| putative anti-sigma factor [Ba... 35 0.019 gi|29347520|ref|NP_811023.1| hypothetical protein [Bacteroi... 33 0.094 gi|29345677|ref|NP_809180.1| two-component system sensor hi... 30 0.47 gi|29346515|ref|NP_810018.1| phosphoglycerate mutase 1 [Bac... 29 1.0 gi|29347070|ref|NP_810573.1| phosphoglycerate mutase [Bacte... 29 1.0 gi|29348342|ref|NP_811845.1| Methionyl-tRNA synthetase [Bac... 28 2.3 gi|29349419|ref|NP_812922.1| DNA-methyltransferase [Bactero... 28 2.3 gi|29348421|ref|NP_811924.1| putative outer membrane protei... 28 2.3 gi|29346850|ref|NP_810353.1| putative outer membrane protei... 28 3.0 gi|29345906|ref|NP_809409.1| TonB-dependent receptor [Bacte... 27 4.0 gi|29347285|ref|NP_810788.1| putative outer membrane protei... 27 5.2

6. Protein Structure Prediction

7. “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

8. Microarray - Measuring Gene Expression of Many Genes at a Time

9. 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

11. 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

12. 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

13. 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

14. 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!!