Metabolomics Lecture Notes

Systems Biology and Metabolomics

  • Systems biology is observation-based, using data mining across various levels (metabolome, proteome, transcriptome, physiological data) to generate hypotheses.

  • Metabolomics aims to identify and quantify all metabolites in an organism, characterizing its phenotype.

  • Challenges: biological variability, harvesting/storage, analytical/extraction methods, compound identification, and data storage.

Key Considerations in Metabolomics

  • Time is a critical aspect, correlating with genome, transcriptome, and proteome.

  • Data quality is paramount; raw data should be accessible to avoid bias.

  • Metabolomics is a tool for answering scientific questions by observing biological systems; a clear question is essential.

Requirements in Metabolomics

  • Extraction of all metabolites.

  • Detection of extracted metabolites.

  • Data set reduction.

  • Identification of metabolites from mixtures.

Sample Preparation

  • Important factors: growing environment, contamination, harvesting time, and tissues.

  • Drying methods: consider water removal, enzymatic degradation, and pH effects; freeze-drying below −80-80 degrees.

  • Ultrasonication facilitates swelling, hydration, and improves diffusion.

Extraction Solvents

  • Plants have >200,000 metabolites with a wide range of molecular weights and polarities.

  • The optimal solvent depends on the target metabolites and resolution.

  • Complete extraction is impossible; aim to visualize differences in extracted metabolites.

Extraction Methods

  • One-step extraction for NMR analysis (proteins removed for animal samples).

  • Multi-solvent extraction: continuous extraction with solvents of increasing polarity.

  • Microorganisms: use precooled 60% MeOH to avoid contamination and sedimentation.

  • Human samples: refrigerate urine with sodium azide; use 0.2 M sodium phosphate buffer (pH 7.4) for NMR analysis.

Analytical Platforms: HPTLC

  • HPTLC standardizes methodology: plate layout, application (spray-on is better), development, detection, and documentation.

  • Factors influencing reproducibility: chamber conditioning and humidity.

  • Derivatization enhances detection, with considerations for time, heating, and drying.

  • Densitometry plots optical density against separation distance, creating a densitogram.

  • SST is needed for each mobile phase to ensure effective standardization.

HPLC Data Evaluation

  • Goal: analyze sample quality and specify compounds.

  • HPTLC is used for quality control of herbals (identity, purity, strength).

  • Untargeted screening identifies compounds and their properties using different solvents.

Chromatography Requirements

  • Separation: wide range of polarity, reproducibility, minimum analysis time, high efficiency.

  • As Detection: high sensitivity, bulk property detection for untargeted, sample-specific for targeted.

  • Resolution factors: retention time and intensity.

HPLC System

  • Pumps: low-pressure gradient mixing.

  • Ultra-HPLC (UPLC): operates at pressures >> 6000 psi/400 bar with low flow rates and short columns.

HPLC Detection Techniques

  • Bulk property detectors, sample-specific detectors, mobile phase modification detectors, and hyphenated instruments (MS).

  • Reversed-phase stationary phases are commonly used.

Reverse and Normal Phase

  • Reverse phase: analytes are more hydrophilic than the stationary phase.

  • Normal phase: analytes are less hydrophilic than the stationary phase (HILIC).

  • Data processing programs: MetaboAnalyst, mzmine, XCMS Online.

LCMS Considerations

  • LCMS systematic variability is often unpredictable; run samples on the same day in random order with quality control.

  • UHPLC is the preferred method for metabolomics: lower run time with optimum resolution.

Multivariate Data Analysis: PCA

  • PCA visualizes data correlations, finding variables of potential importance.

  • Steps: data centering, finding PC1 (new axis), finding PC2 (orthogonal to PC1).

  • If ~70% of the variance is explained, enough information is captured.

  • Variance needs to be visualized in coordinates.

  • Data Scaling in PCA, standardize or normalize the data before applying PCA.

PLS and TCM

  • PLS includes model information, separating response and explanatory variables.

  • Traditional medicine uses herbs with evidence of quality, efficacy, and safety.

  • Plant medicine produces metabolomics under stress with different chemical properties based on origin.

GC-MS Based Metabolomics

  • Temperature-controlled separation of volatile compounds.

  • Compounds are separated by volatility and interaction with stationary phase.

  • Separation performance described by J. van Deemter´s equation.

GC-MS Chromatography and Sample Injection

  • 2-dimensional chromatography solves separation problems.

  • Liquid samples can be injected in split-mode or splitless-mode.

  • Volatile samples can be injected by solid-phase micro extraction (SPME).

GC-MS Chemical Derivatization and Ionization

  • Molecules that are not volatile can be made volatile by chemical reactions.

  • Electron Impact Ionization (EI) generates patterns of molecular fragments.

  • Atmospheric Pressure Chemical Ionization (APCI) maintains the full molecular structure.

GC-MS Mass Spectrometry and Data Processing

  • Ions moved in an electric field to measure exact masses.

  • TOF-MS can be optimized for fast scanning or high mass resolution.

  • Automated and standardized data processing is required.

Recap and Data Processing

  • Sample preparation is critical.

  • LC-MS has high sensitivity but low signal robustness.

  • GC-MS has high resolution and volatility (temperature, derivatization).

  • Data processing involves raw data preparation for MVDA (PCA, PLS).

  • LC-case molecular ion are really small. Alignment data binning or bucketing. Normalization to reduce sample to sample variation.

NMR Based Metabolomics

  • Each metabolite has its own molecular weight.

  • NMR has better resolution compared to NIR and IR.

  • Advantages: quantitative data, everything above detection limit is visible, recognizable fingerprint.

  • Disadvantages: Much less senstive. Less compounds detectable.

  • Pulsed NMR excites all nuclei, and Fourier Transform (FT) obtains the spectrum.

  • Liquid hydrogen is used to prevent the compounds from evaporating.

NMR Spectrum Information

  • Position of signals = chemical shifts; form of the signals = coupling constants; and intensity of the signals = number of nuclei.

  • Improve signal to noise with increased scans, higher concentration, better shimming, and adequate acquisition time.

  • Signal intensity depends only on the absolute quantity of H.

  • Absolute quantification is possible by correlation with any suitable reference compound.
    # Routine procedure for NMR (in metabolomics)

  • A PCA could identify the similarities from the different compounds that were analysed.

  • Calculation similarities using floting bins can be used.

  • Using peaks that are present in one and not in an other.

  • The 0 represent an identical peaks.

NMR Conclusions

  • Similarity reflects any difference in the complete data set.

  • Differential spectroscopy or chromatography shows differences and indicates markers.

  • Identifing the compounds that are responsible for the differences in your dataset.

GCMS Limitations and Fingerprinting

  • GCMS Limitations >> primairy metabolites.

  • Vacuumize the glucose.

  • Measurementes based on isotopically differences with the incorperated carbon.

Biomarkers identification

  • Metabolomics for comparative studies or in-depth metabolome analysis of single/multiple samples.

  • Molecular network allows you to connect metabolites.

LC-MS

  • Most common used method.

  • UHPLC gives a better resolution then HPLC.

  • Molecular networking analysis of the wound response.

LC-MS Basics and Application to Small Molecule Analysis

  • Mass spectrometry: technique that allows for determining the molecular composition of a sample by measuring the masses of the molecules present in it. Every element found in nature has a unique mass. Elements are combined to produce compounds with distinct masses and physical properties. Compounds can be detected by mass spectrometry and thus their masses measured.

  • You could get a mass spectrum on the basis of the exact mas of a molecule. You will get three peaks with the exact masses of the molecule.
    For untargeted metabolomics you could use time of flight as a method. For targeted metabolomics you could use quadrupole.
    The building of an MS
    Sample preparation before LC-MS analysis. You have different column with different possible mobile phases that you could use.

Research examples with LC-MS

Environmental metabolomics: Each organism secretes metabolites to its environment. Each organism has a unique metabolic signature. A better method is needed to monitor the aquatic ecosystems and that could be based on environmental DNA. Isolate DNA from water to detect the fish that was present.

LCMS Remarks.

Liquid Extraction Surface Analysis (LESA). Overall conclusion DESI-MS: reproducibility and sensitivity rather poor.
Spatial info obtainable: objects, TLC plates.

Ambrient Ionisation MS

Fast screening method established for differentiation of THC and CBD.
SPR method for mycotoxins - Mycotoxins could be present in beer. SPR-“biochip spray”-MS. Ug/ml is the sames as 5 ng. Laser Ablation Electrospray Ionisation (LAESI) L AESI-IMS-QTOF-MS - can be used for slices of plant materials but also for other imaging purposes, e.g., animal tissues, TLC plates, petri dishes and well plates.

Plasma-based:

  • Direct Analysis in Real Time (DART) (old method for MS next to DESI). A lot of high molecular weights can not be observed what results in a cleaner peak pattern then DESI. Within second you could get results. For example measuring caffeine in coffee liquid.

  • Sugar is not volatile. It stops somewhere with disaccharides. Polarity starts becoming high then it is not difficult. Easy sugars could be analyzed.

  • An introduction into ambient ionization spectrometry, can provide the molecular weight (MW) of a moleculer. Ambient Mass Spectrometry allows direct sample without probing of a any pretreatment under ambient conditions.Every mass results in one peak

Basics of NMR spectrometry

●Red is the longest wavelength. Energy is lower when the frequency is higher.
Wavelength for NMR -High+Frequency

Structural elucidation of amino acids III Notes

-For counting protons, count how many H+ is present in the structure. Benzene is singlet, with a chemical shift of 7,2.

  • Tyrosine 5 signals in water.

  • Lipids arefatty acids. Figure 4,46. CH3 has a triplet bonding that is a triplet.

  • Ortho 8hz, meta splitting patterns.

Carbon13 NMR

-Both are even number, not magnetic but they are detectable. Electrons are unloyal in other molecules. Frequencies are very turning. In NMR a focus is put on protons to measure the different frequencies. Higer chemical shift > less electron. Close to ten > less electron. Around 0 > more electrons.
BASIC CHEMICAL SHIFT.
Single Basic chemical shift without electron negative is 1 ppm. >>>>>Single bond is 1 ppm. Double basic chemical bond shift is 5 ppm. Doublebond is 5 ppm. >>>>>Triple bond is 2.5 ppm. Triple bond is 2.5 ppm. >>>Aromatic ring is 7.2 ppm. Aromativc Ring>>>>Aldehyde group is always 9.5 ppm.
If solvents are huge in signal then your compound will not be detected. Only methanol could be detected because of the high signal that the solvent has.solving gives specific signals.structural elucidation of sugars Most of sugar resonates are not pure but mixed and they are overlapped with other peaks.Cell walls contain a lot of sugar. Alpha (down) and beta (up) glucose are the same. Alpha (down) and beta (up) glucose are the same. In the lab glutamic acid is really high. It is a precursor from glucose. Glycine is overlapped with other sugars in NMR.

Translational Metabolomics/Lipidomics Current Applications and Future Opportunities

-Metabolites are (not just a molecule).a combination of technology and biologyYou could use molecule information to monitor drug responses and for example identify diseases.GC-MS was first used with paper chromatography, where fingerprinting was invented. Lipids could be studied as a metabolomics.Lipidyzer. Headgroups are bound to sidechains to identify lipids.Lipids like to dissolve in organic solutions. Lipid classes could be identified.Mutations and try to find pathways involving in disease mechanisms. This software was developed is NLA.With NLA. Lipids could be measured. Make mutations and try to find pathways involving in disease mechanisms. NEUROLIPID atlas. Nerves do not communicate correctly with the muscles. C9 is a mutation that could result in ALS.Multiomics: all techniques are used to get an overall detailed view of the metabolomics: Pipeline for studies of metabolism in cells and tissue organoids have different lipid layers.All the different organoids have different lipid layers

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