Metabolomics Part 1

1. MetabolomicsPart 1 PCB 5530 Fall 2017

2. Metabolomics Day 1 • Introduction to Metabolomics: • Basics & limitations of metabolomics • Sample preparation • Chromatography Day 2 • Mass Spectrometry in metabolomics Day 3 • Metabolomics data analysis

3. Definitions and Background Metabolome = the total metabolite pool • All low molecular weight (< 2000 Da) organic molecules in a sample such as a single cell, leaf, fruit, seedling, etc. Sugars Nucleosides Organic acids Ketones Aldehydes Amines Amino acids Small peptides Lipids Sterols Terpenes Alkaloids

4. Definitions and Background Metabolomics = high-throughput analysis of metabolites Metabolomics is the simultaneous measurement of the levels of a large number of metabolites (typically several hundred). However, due to the complexity, any of these are not identified (i.e. are just peaks in a profile).

5. Definitions and Background

6. Definitions and Background Scope Accuracy Untargeted Metabolomics -measures many compounds (Ratios) Metabolic profiling -measures a set of related compounds (e.g. phosphate esters) Targeted analysis -measures specific compounds; (Quantitation)

7. How old is the field of metabolomics? Profiling of blood and urine for clinical detection of human disease has been carried out for Centuries. Ulrich Pinder, 1506: EpiphanieMedicorum Urine wheel describes possible colors, smells and tastes of urine Nicholson, J. K. & Lindon, J. C. Nature 455, 1054–1056 (2008).

8. How old is the field of metabolomics? • Advanced chromatographic separation techniques developed in late 1960’s. • Linus Pauling published “Quantitative Analysis of Urine Vapor and Breath by Gas-Liquid Partition Chromatography” in 1971 • Chuck Sweeley at MSU helped pioneer metabolic profiling using gas chromatography/ mass spectrometry (GC-MS) • Plant metabolic biochemists (e.g. LotharWillmitzer) were among other early leaders in the field. # of metabolomics publications  Metabolomics is expanding to catch up with other multiparallel analytical techniques (transcriptomics, proteomics) but remains far less developed and less accessible.

9. The Metabolome: Size and Concentrations All Mammals All Microbes All Plants 8000 Chemicals 20,000 Chemicals 200,000 Chemicals • All plant species combined contain on the order of 105 compounds. • Individual plant species are estimated to contain 5,000 – 30,000 compounds • Ratio of metabolites/genes much smaller than in microbes • Metabolic profiling much harder than in other organisms The Pyramid of Life

10. Power of Metabolomics Silent Knockout Mutations. • ~90% of Arabidopsis knockout mutations are silent (no visible phenotype) • ~85% of yeast genes are not needed for survival • Metabolic Control Analysis: • Growth rate (sum of all metabolic fluxes) is unchanged in silent knockout mutations • Pool sizes of metabolites can change to compensate for effect of mutation, metabolic fluxes are unchanged •  this can be measured!

11. Power of Metabolomics Silent knockout mutations Example. • Chloroplast 2010 project (phenotype analysis of knockouts of Arabidopsis genes encoding predicted chloroplast proteins): • Various knockouts showed essentially normal growth and color but highly abnormal free amino acid profiles, e.g. At1g50770 (‘Aminotransferase-like’)

12. Why Metabolomics is Difficult Metabolomics Proteomics Genomics 105 Molecules Chemical Diversity 20 Amino acids 5 Bases The Pyramid of Life

13. Why Metabolomics is Difficult • Concentrations of cellular metabolites vary over several orders of magnitude (mM to pM) • Differences in molecular weight (20-2000 Da) Concentration Response Metabolomics • High turnover rates • Some metabolites are labile Concentration Response Proteomics Concentration Response Genomics Time

14. Why Metabolomics is Difficult Dihydrozeatin riboside monophosphate <1 fmol mg-1leaf fresh weight Sucrose Cytosolic concentration as high as 50mM in spinach leaves

15. Metabolomics Steps in metabolomics sample preparation sample extraction chromatography detection data analysis

16. Sample Preparation Growth/Sample Size • Grow organisms (e.g. plants or bacteria) under identical conditions • Randomize the treatment groups (Make sure effects are measured due to variability in samples, not in experimental set up • number of replicates… depends on what you want to find • Large differences = small replication needed • Small differences = large replication needed • In general, a minimum of six replicates for each treatment are needed (due to high biological variability) Grow more than you think you’ll need!

17. Sample Preparation Biological replicates: High variability, but “this is life” Technical replicates: “Is your sampling/ extraction method robust?”

18. Sample Preparation Sample collection • Uniform sample sizes (e.g. hole punches in leaves) • Be consistent - similar tissue - time of day • Quickly freeze sample in liquid nitrogen, store samples at -80°C • Fast-harvesting method for bacteria (~30 sec)

19. Sample Extraction Choosing an extraction method • No universal extraction method exists • Some solvents may degrade certain compounds • Its good to have some idea of what metabolites you want to extract: Untargeted metabolomics / Metabolic profiling / Targeted analysis

20. Sample Extraction Choosing an extraction method Physical disruption: Grind by hand? Mechanical? Extraction efficiency Extraction time How do you check for sufficient extraction?

21. Sample Extraction Sample extraction • The method should be consistent and reproducible • Further workup may be required; esp. for targeted analysis (e.g. solid phase extraction)

22. Sample Extraction Why is it particularly difficult in plants? • Plants are tough! • Plants contain tissues made up of complex polymers that are difficult to homogenize (e.g. lignin, cellulose, starch). • Homogenizing roots is much more difficult than E. coli • These structural polymers also contain metabolites which are difficult to extract • Plant leaves are made up of ~30 different cell types, so incomplete homogenization can lead to high variability • Plants contain a wider variety of metabolites (both in number and chemical composition) than most organisms.

23. Chromatography introduction • Invented in 1900 by Mikhail Tsvet (used to separate plant pigments) • Types include: - TLC (thin-layer chromatography) - GC (gas chromatography) - LC (liquid chromatography) Y GC and LC are routinely used in metabolomics

24. Chromatography Principle of chromatography Principle: Separation of compounds based on differential partitioning between solid and mobile phases. https://www.khanacademy.org/test-prep/mcat/chemical-processes/separations-purifications/a/principles-of-chromatography

25. Chromatography Gas Chromatography • GC = ‘good chromatography’ • Separation according to difference in volatility & structure • For compounds with sufficient volatility • thermostable

26. Chromatography Gas Chromatography • Mostly used for untargeted metabolomics • optimized over several decades • High reproducibility • Easy to use • Good software • ‘standardized’ GC method with very good databases for compounds identification • Very universal for compounds <600 Da • Great coverage for polar compounds (for same coverage, 3+ LC-MS methods are needed • Only tool for volatiles Limitations: - high temperatures can destroy labile compounds - polar compounds cannot ‘fly’ on GC columns and must first be derivatized - difficult to collect fractions - heat may cause degradation

27. Chromatography GC Profile Retention time [min]

28. Chromatography Sample derivatization Step 1) Methoximation Step 2) Silylation Z/E isomer have same mass spectrum but differ 2 seconds in retention time Gas chromatography requires volatile compounds (two step derivatization in vial) • 1) Methoximation of aldehyde and keto groups (primarily for opening reducing ring sugars) • 2) Silylation of polar hydroxy, thiol, carboxy and amino groups with silylation agent MSTFA • A single compound with multiple active groups will result in multiple peaks (1TMS, 2TMS, 3TMS) • GC-MS can distinguish between stereoisomers Anal Chem. 2009 Dec 15;81(24):10038-48. doi: 10.1021/ac9019522. FiehnLib: mass spectral and retention index libraries for metabolomics based on quadrupole and time-of-flight gas chromatography/mass spectrometry. Kind T, Wohlgemuth G, Lee do Y, Lu Y, Palazoglu M, Shahbaz S, Fiehn O.

29. Chromatography Liquid Chromatography LC = ‘Lousy chromatography’ Mobile phase: Liquid Analyte separation based on difference in interaction with column & mobile phase For small and macro-molecules, ionic compounds (not volatiles) Thermostable & thermolabile compounds

30. Chromatography Liquid Chromatography LC = ‘Lousy chromatography’ • Relatively new, recent advantages • Thousand of columns available… normal phase, reverse phase, ion exchange, HILICNew columns constantly being developed to improve resolution, sensitivity and run time • Infinite solvent systems possible:Selection of chromatographic configuration depends on physicochemical properties: solubility, polarity, weight • Separation is based on complex interaction of analytes with column and mobile phase • Advantages: compound can be collected after separation derivatization not necessary a separation protocol can be optimized for nearly any compound • BUT: Low reproducibility  no massive databases

31. Chromatography LC Profile Retention time [min]

32. Chromatography Liquid Chromatography LC = ‘Lousy chromatography’

33. Chromatography What to use for what compounds? (Reversed Phase High Performance Liquid Chromatography) RP-HPLC GC (Gas Chromatography) HILIC (Hydrophilic Interaction Chromatography) Non-polar vitamins Volatile organic compounds Amino/organic acids Sterols Fatty acids Sugars Triglycerides Very polar Polar Medium-polar Non-polar