PDF Metabolite profiling in blood plasma - Fiehn Lab - Home

  • Pdf File 592.85KByte

´╗┐Metabolite profiling in blood plasma

Oliver Fiehn, Tobias Kind UC Davis, Genome Center 5 GBSF Building, 451 East Health Sciences Drive, Davis (CA), USA Email: ofiehn@ucdavis.edu , phone: +1-530-754-8258

Key words: mass spectrometry, GC-MS, metabolomics, data mining, diabetes

10 Abstract

Metabolite profiling has been established as a multiparallel strategy for relative quantification of a mixture of compounds or compound classes using chromatography and universal detection technologies (GC-MS, LC-MS). Despite its origins dating back to the late 1960's, it 15 was only in the 1980's that its use was acknowledged to diagnose metabolic disorders in men, especially for rapid screening of inborn errors. Even faster ESI-MS/MS screening methods replaced longish chromatographic methods, and method development had stopped despite its potential use for other, less imminent diseases such as likelihood assessments of type II diabetes mellitus or cardiovascular risk factor evaluation. In addition to its diagnostic use, 20 profiling blood samples can be employed to investigate specific biochemical responses. The broader scope of analysis outweighs the disadvantages by taking compromises in method development and the reduced accuracy for specific metabolites. This chapter exemplifies the strategies in metabolite profiling by GC-MS. It gives experimental details on basic steps like blood plasma withdrawal, storage, protein precipitation, extraction, concentration, 25 derivatization, data acquisition, raw data processing and result data tranformation. A major difference to profiling plant tissues is that no fractionation step is utilized, enabling the analysis of primary metabolites like sugars and amino acids concomitant with lipids such as sterols and free fatty acids.

Fiehn and Kind:

Metabolite profiling in blood plasma

30 1. Introduction

Metabolite profiling is an analytical method for relative quantification of a select number of metabolites from biological samples (1), i.e. members of specific pathways or compound classes. In plant biology, samples have been garnered from a specific tissue or a part of a 35 tissue of interest, but for biomedical purposes, analysis of metabolite profiles in body fluids such as blood, urine or saliva, is equally important. Metabolite profiling is distinguished from other analytical procedures by its scope:

(a) Target analysis is constrained to one or a very few target compounds (such as

40

hormones). Such targets are usually quantified in an absolute manner using calibration

curves and/or stable isotope labeled internal standards.

(b) Metabolite profiling restricts itself to a certain range of compounds or even to screening

a pre-defined number of members of a compound class. Within these constraints, a

single analytical platform may be sufficient. Examples might be the analysis of

45

carotenoid intermediates by liquid chromatography/diode array UV detection (HPLC-

UV), or sugars, hydroxy ? and amino acids by fractionation and gas

chromatography/mass spectrometry (GC-MS), or vitamin profiling by HPLC-MS/MS.

Quantification in metabolite profiling is usually carried out relative to comparator

samples, such as positive and negative controls.

50 (c) Metabolomics seeks for a truly unbiased quantitative and qualitative analysis of all

biochemical intermediates in a sample. It must not be restricted by any physicochemical

property of the metabolites, such as molecular weight, polarity, volatility, electrical

charge, chemical structure and others. Since there is currently no single technology

available that would allow such comprehensive analysis, metabolomics is characterized

55

by the use of multiple techniques and unbiased software. Metabolomics also uses

relative quantification. In addition, it must include a strong focus on de novo

identification of unknown metabolites whose presence is demonstrated.

(d) Metabolite fingerprinting is different from the other three approaches in that it does not

aim to physically separate individual metabolites. Instead, spectra from full sample

60

extracts are acquired by a single instrument (such as 1H-NMR). Spectra are then

compared by multivariate statistics in order to find spectral regions that discriminate

samples by their biological origin. In some instances, these regions may again point

2

Fiehn and Kind:

Metabolite profiling in blood plasma

towards specific metabolites; in general, however, one dimensional methods are restricted in resolving complex mixtures. 65 Metabolite profiling therefore must be seen as a compromise between truly quantitative target analysis and completely unbiased metabolomics. Each metabolite profiling method is directed towards a chemically very different compound class, hence there are various methods published depending on the actual task. In itself, each procedure will be a compromise 70 between several parameters such as compound stability, solubility, influence of the cellular matrix, time needed to carry out the protocol, constraints given to garner samples (blood withdrawal), extraction (potentially followed by fractionation), submission to analytical instruments, raw data analysis and statistics. For example, a protocol found to be well suited for the analysis of oxylipids in urine will be very much different from one that aims at 75 hydrophilic sugars and amino acids in blood plasma. Validation criteria for metabolite profiling protocols are therefore different from target analysis: (a) Reproducibility (precision of relative metabolite levels) is more important than absolute recovery. (b) Robustness and practicability are more important than accuracy (correctness in absolute metabolite concentrations). (c) Comprehensiveness is more important than inclusion of a certain 80 metabolite that might be missed. (d) Overall dynamic range for the majority of compounds is more important than the detection limit for a specific substance. (e) On contrary, the ability to include important known key metabolites may still be more important than the detection of unidentified peaks that might be biochemical side-products of enzymes with low substrate specificity. 85 Obviously, these considerations can only serve as guidelines and must be weighed for importance when new methods are developed, explicitly stating which criteria were regarded most important and why. This refers to the need of exact definitions of the scope of an analytical method (2), which is dependent on the research area to which it is applied.

90 In this chapter, a validated method for metabolite profiling of primary metabolites and sterols is elaborated for blood plasma matrix. Analysis of lipophilic components such as (unsaturated) free fatty acids and sterols is regarded equally important to sugars and hydroxy acids in medical diagnostics, therefore, classical metabolite profiling techniques that made use of inexpensive and mature technologies (such as GC/quadrupole MS) needed to be replaced

95 by more sophisticated setups. The basic steps in the process can be summarized as:

3

Fiehn and Kind:

Metabolite profiling in blood plasma

1. Design an experiment according to the biological question. Use randomization

wherever possible. Use preexisting knowledge to target the number of individuals to

be tested: generally, biological variation among humans exceeds greatly the variation

100

found in animals. If there is not enough information available about (metabolic)

variation in your test populations, consider small test experiments to gather such

values. Consult statisticians before carrying out the experiments!

2. Collect as much background information about your individuals or animals as

possible: this will later aid interpretation of data. This includes any data that

105

potentially may have an effect on the measured variables, for instance: genotype

(gender, ethnicity/line, SNPs, progeny etc), phenotypic descriptions (e.g. images,

weight, body mass index, waist-hip ratio, size etc), environmental impacts

(food/nutrition, health status, drug treatments, physical exercise, mental status/stress,

fasting state etc.)

110

3. Withdraw blood using standard procedures into EDTA-containing tubes. Freeze at -

20?C after blood withdrawal. Do not use samples that have been thawn more than

twice.

4. Extract blood plasma in a comprehensive and mild way concomitant with enzyme

inactivation and addition of internal standards.

115

5. Dry down an aliquot of extract, and keep the other aliquots frozen for record purposes.

6. Derivatize the extract by first adding methoxyamine in an aprotic basic solvent, and

then adding a trimethylsilylating agent.

7. Analyze the derivatized sample by direct thermodesorption GC-TOF.

8. Process the raw GC-TOF data.

120

9. Normalize and transform the result data, and perform statistical evaluations.

The basic theoretical considerations behind this process are quite simple: the measured metabolite levels should reflect the in vivo state which need background information for interpretation of metabolic changes (and variation). Therefore, any metabolic variation by 125 formation of chemical or post-harvest biochemical artifacts must be prevented. Biochemical inactivation can be ensured by coagulation of enzymes, either using heat-shock or cold-shock methods, with the help of organic solvents such as chloroform, acetone, isopropanol or acetonitrile that force protein precipitation. Conversely, chemical artifact formation depends on the stability of each specific compound and is therefore hard to predict. Generally, any 130 harsh treatment of the metabolome mixture should be avoided. Instead, conditions for

4

Fiehn and Kind:

Metabolite profiling in blood plasma

extraction, storage, chemical derivatization and analysis should be as mild and as comprehensive and universal as possible. In this respect, cold treatments are generally preferred over heat treatments.

135

2. Materials

2.1 Blood plasma collection A notebook in electronic or paper format is needed to keep track on sample identity numbers, fasting state, day, time, and physiological parameters. Vacutainer safety equipment for 140 collection of blood plasma samples should be used, withdrawing blood directly into K3EDTA lavender-top tubes. Spare tubes and a centrifuge capable of 3000 g centrifugation to separate plasma from blood cells are needed. Micro centrifuge tubes and a vortexer are employed for aliquotation and homogenization. Dewars with liquid nitrogen will ensure the immediate arrest of residual biological activity after centrifugation. Dry ice and a -80?C freezer are 145 needed to ensure plasma stability during storage and transportation.

2.2 Extraction For rinsing or cleaning dishes, only ultra-pure water with a level of total organic carbon TOC99% ultra-pure HPLC-MS gradient grade purity) is used and stored at room temperature in 155 the dark. A pH measurement device will be needed to check neutrality of solvents. Volumes are measured using calibrated pipettes whose accuracies are subjected to quality control routines at least once every six months. An ice bath and liquid nitrogen dewars are used for temporarily storing samples during the process. Large twisters are useful to operate in nitrogen dewars. Extraction is performed in a micro centrifuge tube shaker. 160 2.3 Derivatisation A speed vacuum concentrator or lyophilizer is used for drying extracts to complete dryness. A mixture of 40 mg/mL of methoxyamine.HCl in pyridine (p.a. quality) is freshly prepared using an ultrasonicator. In case ATAS (NL) liners are used, pyridine must be exchanged

5

................
................

In order to avoid copyright disputes, this page is only a partial summary.

Online Preview   Download