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Flashcards in Omics Deck (27)
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1
Q

key omics most pertinent to biotechnology

A
  • genomics
  • transcriptomics
  • proteomics
  • glycomics
  • kinomics
  • metallomics
  • metabolomics
2
Q

the central dogma

A

DNA –> RNA (intermediatory but still a store of info) –> proteins

3
Q

define and ome and omics?

A

omes:
genome (DNA) (stable in organism) –> transcriptome (RNA) (responds to changes in signals) –> proteome (proteins) (responds to changes in the transcriptome and post translational modifications) –> metabolome (metabolites) (changes in response to proteins and metabolites in the cell)
omics: the studies of these so…
Genomics –> transcriptomics –> proteomics –> metabolomics

4
Q

the human genome?

A
  • took 20 years to sequence

- is printed in the welcome trust library

5
Q

Genomics: Fred Sanger

A
  • the study of genes and their function
  • first to start genomics and sequenced insulin by edmund sequencing and then invented sanger sequencing which meands we can sequence DNA
6
Q

Genomics: Hagen Bailey

A
  • if you put DNA through an outer membrane bacterial pore you can measure the current, different bases give different currents = nano pore technology
  • means we can sequence lots of DNA v. quickly
  • minION - as its advanced the size has got smaller
  • better than Sanger sequencing but different technologies compliment eachother
7
Q

Next-Gen Sequencing?

types and advantages/disadvantages

A
  • modern technologies for sequencing genomes
  • different technologies have different advantages; cost per base, read length, sequence preparation; you cant just use one method
    1. Sanger sequencing: long accurate reads but high cost
    2. 454 pyrosequencing: intermediate reads and intermediate cost (common method)
    3. Illumina dye sequencing: massively parallel, long reads
    4. SOLiD: sequencing by ligation
    5. Ion torrent: semiconductor-based
    6. Nanopore: MinION: current changes as DNA passes through nanopores, big inaccurate reads
  • we take technologies that produce long inaccurate reads and then map our shorter more accurate reads to them
8
Q

comparative genomics:

A
  • understanding the organisation of genes and genomes within and between organisms
  • interested in genes that encode proteins - Open Reading Frames
  • sequence genomes and map them together to compare what protein coding genes one has that the other doesn’t
  • use bioinformatics analysis to look at databases
  • take those genes out, clone them, put them in the one that doesn’t and see if it changes how they are
9
Q

meta-genomics

A
  • study of genetic material recovered from environmental samples without being able to culture the organisms they come from
  • we cant culture all organisms but we want to look at the DNA
  • so we sequence it and look for protein coding genes
  • discovery of useful enzymes
  • Jo Banfield; work on unculturable archaea - has expanded the tree of life
10
Q

Synthetic genomics

A
  • next-gen sequencing coupled with large-scale DNA assembly
  • codon optimisation - re-use redundant codons to do other things
  • Amber-codon (stop codon) reuse - using it for unnatural amino acids
  • George Church; professor of molecular biology at Harvard, wants to perform de-extinction, Wooley Mammoth in particular as living close relative
  • ‘Human Genome Project Right’ - can we build a human genome from scratch, take out disease causing genes (ethics)
11
Q

synthetic genomics: what can we learn from building a genome?

A

taking it apart and put it back together we can see:

  • essential genes
  • essential non-coding sequences
  • role of introns/ alternative splicing in genes
  • DNA replication elements
  • role of the 3D organisation of a genome - learn a lot about gene regulation
12
Q

Functional Genomics

A
  • understanding biological functions through use of genomic/transcriptomic data
  • omics are dynamic; transcription, translation, regulatory, protein:protein interactions
  • investigate functions of cells and assigns functions to genes
13
Q

Methods in Functional Genomics:

Transcriptomics?

A
  • the set of all the mRNAs in a cell
    methods:
  • northern blot
  • RT-qPCR
  • ddPCR
  • DNA microarrays
  • RNA-seq
14
Q

functional transcriptomics methods: northern blots?

A
  • take a sample (cells/tissues)
  • take out delicate RNA
  • run it via electrophoresis; RNA separated by size
  • do northern blotting (transfer of RNA to a membrane)
  • place on labelled probes (radioactive/fluorescence)
  • visualisation of labelled RNA on X-ray film or phosphorescent screens
  • quantify how much RNA you have so therefor how much gene expression
15
Q

functional transcriptomics methods: RT-qPCR?

A
  • reverse transcriptase quantitative PCR
  • doesn’t rely on radiation
    1. revers transcriptase (with poly-T primer) that can convert RNA to DNA and amplify mRNA
    2. DNA amplification and fluorescence detection (qPCR machine has a fluorescence detector on top) - add fluorescent probes and as they get broken apart the fluorescence level goes up (more abundant RNAs fluorescence increase earlier)
  • can look at low abundance RNAs by looking at the relative abundance of RNA based on the fluorescence
16
Q

functional transcriptomics methods: ddPCR?

A
  • PCR reaction partitioned into 20,000+ droplets with oil
  • tells you actually how many molecules of RNA there is
  • separates RNAs out into individual drops containing 1 RNA molecule which we measure = exact quantification of RNA
  • expensive and technically challenging
17
Q

functional transcriptomics methods: Microarrays?

A
  • specific DNA fragments immobilised on a chip. Hybridisation with labelled probes to measure gene expression
  • comparative genomic hybridisation
  • expensive
    1. RNA extracted
    2. reverse transcriptase - DNA
    3. label DNA with dye
    4. hybridise it to DNA stuck to chip
    5. scan with laser scanners
    6. normalise it to known probes (control) and look at levels of changes in gene expression
18
Q

functional transcriptomics methods: Protein arrays?

A
  • microarray technique fallen out of favour
  • mRNA levels don’t always correlate with levels of protein in cells
  • protein arrays quantify levels of proteins on a chip
  • used for: detection of biomarkers, protein:protein interaction analysis, antibody characterisation
19
Q

functional transcriptomics methods: carbohydrate arrays?

A
  • immobilising different carbohydrates on functionalised surfaces
  • identify plant cell walls; determines the provenance of food (sugars) and wood (prove if your being sold the correct products)
20
Q

functional transcriptomics methods: RNAseq

A
  • super-seeded microarrays
  • its a much higher through-put than rt-qPCR
  • next-gen sequencing of whole transcriptomes
    1. RNA - reverse transcriptase - cDNA
    2. sequence it; with adapters onto ends to allow the sequencing platforms to read them
  • lots of data, hard to analyse
  • used often but hard to understand the data
  • powerful method; can look for where introns/exons/transcriptional start sites are
21
Q

structural proteomics?

A
  • early 2000’s project to determine structures of proteins with unknown structure/function
  • protein fold is better conserved than sequence
  • 30-40% of ORFs in sequenced bacterial genomes had no structural homologue in the PDB - goal was to fill this knowledge gap
  • methods; x-ray crystallography, NMR, Cryo-EM
    Key technologies:
  • genome sequencing
  • High Throughput cloning methods
  • Optimised protein expression systems
  • high capacity protein purification equipment
  • miniaturised protein crystallisation robotics - decreases the amount of sample needed (nano litre pipetting robots means we can do more with same amount of protein)
  • 3rd generation synchrotron light sources
  • Fast 3D-capable computers, cheap data storage
22
Q

Metabolomics?

A
  • study of small molecule components of cells/culture media
  • not proteins/DNA/RNA
  • we need to look at the metabolism of cells to perturb it
    sampling:
  • stop the biochemistry (cooling/filtration)
  • aqueous extraction
  • organic extraction
    analysis:
  • separation: High Pressure Liquid Chromatography and Gas Chromatography
  • identification:
    Chromatography-linked detectors (UV/VIS monitor / Conductivity monitors / Fluorescence monitor), Mass spectrometry = gold standard, NMR (assigns chemical structure of molecule)
23
Q

Metabolomics: separation: chromatography?

A
  • size exclusion chromatography
  • glass column packed with beads (acrylamide/silica medium) with holes
  • mixture (liquid, gas etc) goes down column
  • small molecules can enter the matrix of chromatography medium and take longer to get down than large which don’t enter the medium (elute sooner)
  • separation doesn’t have to be chromatography, can be gel-based
24
Q

Metabolomics: identification: Mass spectrometry

A
  • chromatography system connected to a mass spectrometer
  • standard method = electrospray ionisation
  • liquid fired out of nozzle at high voltage; charges up the peptides
  • this ionisation leads to gain or loss of proton or multiple protons
  • always +/- charged ions
  • high vacuum systems with magnets in them which guide the molecules through a tube
  • mass analyser = charge reading device
  • measure a plot of mass over charge peaks
  • naturally occurring isotopes complicates mass-spectrometry
  • do statistical analysis on the mass/charge peaks
25
Q

metallomics

A
  • study of free metals and metalloproteins in cells and cellular compartments
  • how do proteins get the right metals
  • 20% of enzymes need a metal co-factor
    methods:
  • rely on physical properties of metals; electron/x-ray scanning, ionisation, mass
  • ICP-MS
  • X-ray fluorescence
  • high-resolution transmission electron microscopy (electronic properties of metals)
  • energy dispersive x-ray spectroscopy (electronic properties of metals)
26
Q

metallomics: Irving-Williams series?

A
  • the sequence of complex stability of the first transition metals
  • describes ability of the transition metals to form coordinated complexes

Mn2+ -> Fe2+ -> Co2+ -> Ni2+ -> Cu2+ -> Zn2+

  • if a metalloprotein gets the wrong metal, nothing happens
  • where the metal is folded influences the metal content it gets
27
Q

metalloproteomics?

A
  • actively coupled pasma mass spectrometry
  • acceleration of sample through argon plasma
  • highly sensitive detection of metal ions
  • usually using a Quadrupole MS
  • anion exchange chromatography followed by size-exclusion gel-filtration chromatography then ICP-MS
  • 2D plots of size against isoelectric point
  • PCA used to correlate protein with metal content
  • confirm it experimentally by gene knockout
  • 2 proteins identified: MncA, CucA (manganese and copper binding protein); had similar metal binding sites
  • MncA was found to prefer copper
  • metals getting to the right protein is vital for function