UCL Biochemistry for Biochemical Engineers Lecture 22 Omics PDF

BENG0004 Biochemistry for Biochemical Engineers Jack Jeffries Lecture 22 Omics  Omics There are now many –omics technologies: Genomics – the use of DNA sequencing, recombinant DNA techniques, genetics e...

BENG0004 Biochemistry for Biochemical Engineers Jack Jeffries Lecture 22 Omics  Omics There are now many –omics technologies: Genomics – the use of DNA sequencing, recombinant DNA techniques, genetics etc to understand the full genome of an organism Transcriptomics – analysing the full complement of mRNA of a cell. Can be very useful in looking at responses of a cell to treatments such as a drug or virus infection Proteomics – analysing the entire set of proteins synthesised by a cell at a particular time. Like transcriptomics it can show responses to external stimuli. Metabolomics – analysing the full set of metabolites of a cell. Can be used to determine the flux through pathways. Also used in diagnostics nowadays. Lipidomics – analysing all the lipids in a cell. Can be used in studying normal versus disease states such as stroke, hypertension, Type II diabetes, heart attack, obesity. Genomics – the use of DNA sequencing, recombinant DNA techniques, genetics etc to understand the full genome of an organism. The use of Next Generation DNA sequenceing with Roche 454, Illumina, PacBio and other machines means that entire human genomes can be sequenced and compared to a reference genome sequence. This is used to look at SNPs – single nucleotide polymorphisms. SNPs can be seen in many genes and in the DNA outside genes. They can correlate with certain diseases. An example is a single base mutation in the APOE (apolipoprotein E) gene is associated with a higher risk for Alzheimer disease. Other SNPs occur and are involved sickle cell anemia, cystic fibrosis and many cancers. SNPs can be used to look for genome wide associations of the positions of SNPs and correlate these with different diseases.  Genomics – DNA sequencing assembly or not? Initial DNA sequences Each long contig is Assemble into long still only a tiny part of contigs the genome Human genome is 3.3 x 109 base pairs. Full assembly and annotation still takes many hundreds of human hours. Just comparing SNPs to a reference genome takes minutes. Transcriptomics – analysing the full complement of mRNA of a cell. Can be very useful in looking at responses of a cell to treatments such as a drug or virus infection mRNA is isolated from cells and converted to cDNA. This is a DNA copy of the mRNA. [cDNA is copy DNA] Fluorescent labels are introduced during this mRNA to cDNA Cells from another time point or cells that have been treated with a drug or hormone have their mRNA extracted and cDNA made with a different fluorescent label. The two cDNA preps are hybridised to gene chips containing synthetic oligonucleotides corresponding to parts of the expressed gene complement, introns, exons etc. Gene chips are also called microarrays  Proteomics – analysing the entire set of proteins synthesised by a cell at a particular time. Like transcriptomics it can show responses to external stimuli. Used to be done using 2-D gels. Then individual spots were cut out and digested with trypsin and put into an LC-MS A MALDI-MS Matrix assisted time of flight-mass spectrometer  2D gel of rat liver cells. The identity of certain proteins is shown from their known positions of size and charge. Some proteins occur in several spots due to different levels of phosphorylation and other post translational modifications. Size kD large Small 4 pI 10 2D gel separation of E. coli proteins Protein spots from a 2D gel can be put through a tandem mass spectrometer. MS/MS This separates the proteins in the first stage MS and then fragments each peak in the second stage MS. The characteristic fragment pattern is seen by a computer and the identity of the protein determined Metabolomics – analysing the full set of metabolites of a cell. Can be used to determine the flux through pathways. Also used in diagnostics nowadays.  How to analyse? RNA and Proteins have common properties so a technique can be developed that is generic for all RNA or all proteins. For a cells entire set of metabolites this is more difficult as the properties of the metabolites differ markedly. Hydrophilic Hydrophobic Volatile Charged Amphipathic Short half life Metabolomics has 4 phases: 1) An extraction method that preserves the compounds 2) A separative method - gas chromatography, high pressure liquid chromatography or capillary electrophoresis to separate metabolites 3) mass spectrometry or NMR to identify the metabolites 4) Computational tools to analyse the data What can metabolomics tell us? By comparing a control sample with a test sample we might see the consequences of a disease. The serum of a person can be analysed for its entire set of metabolites and this can be compared with a database of normal and diseased states. The ‘fingerprints’ of different diseases can be built up in such databases. An example is diabetes “The advantage of metabolomic analysis is that the biochemical consequences of mutations, changes in the environment and treatment with drugs can be observed directly. This may help in the development of new drugs. It may also help us to understand how drugs work, interact and cause side effects.” From the Wellcome Trust The human genome - like many others - has 20-30% of its open reading frame with no known function. Metabolomics can help to reveal the functions of some of these gene products. There are approximately 2900 endogenous or common metabolites that are detectable in the human body. Not all present in the same tissue as different tissue have different metabolic roles. The Canadian human metabolome project has identified and quantified (i.e. determined the normal concentration ranges for) 309 metabolites in Cerebrospinal Fluid, 1122 metabolites in serum, 458 metabolites in urine and approximately 300 metabolites in other tissues and biofluids. Over 50,000 metabolites are known from plants putting in perspective our knowledge of human metabolic biochemistry. Can be used in discovery – then in diagnosis or treatment. Two novel biomarkers which are elevated in heart failure patients. Pseudouridine and 2-oxoglutarate [same as 2-ketoglutarate]  Using metabolomics for Metabolic flux analysis. Use 13C labelled glucose to feed a cancer cell line. Metabolites are extracted in ice cold methanol Derivatised to make them volatile Run on GC-MS (gas chromatography to separate and mass spectrometry to identify. Experimentally determined fluxes representing central carbon metabolism in tumor cells. Net fluxes are listed first for each reactionand exchange fluxes are within parenthesis. Units for all fluxes are nmolmin−1 andmgprotein−1. Italicized numbers represent flux values that were taken from the literature since they were unidentifiable in this particular experiment. Some examples. 2 kinds of mouse - conventional (conv) and germ free (GF) A study of the effect of the gut microbiome on serum metabolites. 10 samples each of GF and conv mice, methanol Liquid chromatography, mass spectrometry protein precipitation and centrifugation and the supernatants were analysed by 4 different methods. Numbers of metabolites in the serum 3975 are found in both conventional and germ free mice. 145 are found only in conventional mice, 52 found only in germ free mice The microbiome affects the diversity of indole-containing compounds in the serum Metabolite Fold change Tryptophan 1.7 GF N-acetyltryptophan 2,4 GF Serotonin 2.8 conv Tyrosine 1.44 GF Hippuric acid 17.4 conv Phenylacetylglycine 3.8 conv IPA only seen in conventional Phenyl sulfate II p-Cresol sulfate II Phenylpropionylglycine II Cinnamoylglycine II Indole-3-proprionic acid (IPA), also identified only in the plasma of conv mice, has been shown to be a powerful antioxidant, and is currently being investigated as a possible treatment for Alzheimer's disease.  Indole containing metabolites Indole-3-proprionic acid  Glycine containing metabolites Not listed in any metabolite database  Key Points to know What all the different omics measure – genomics, metabolomics etc Which techniques are used for which e.g. DNA sequencing for genomics, LC-MS for proteomics