C OMPARISON OF METHODS

Both, amino acid analyzer and iTRAQ^®-LC-MS/MS require protein precipitation.

GC-MS allows the direct derivatization of amino acids with propyl chloroformate in native urine and, therefore, automation of the entire analytical procedure.

The urine volumes needed for GC-MS and iTRAQ^®-LC-MS/MS analysis are 40-50 µL, while 200 µL are required for the amino acid analyzer. Given that urine is typically available in large quantities, these differences in sample volume are negligible.

A drawback of the amino acid analyzer is the typical runtime of 130 min. In contrast, total runtimes for GC-MS and iTRAQ^®-LC-MS/MS are 20 and 25 min, respectively. The LLOQs for the amino acid analyzer (2-3 µmol/L) are also on average higher than those for GC-MS (0.3-30 µmol/L) and iTRAQ^®-LC-MS/MS (0.5-10 µmol/L).

A disadvantage of GC-MS is the smaller number of amino acids amenable to analysis. In principle, 33 urinary amino acids can be detected by GC-MS, but only 22 amino acids were measurable above the LLOQ in ≥ 80% of the 144 urine specimens of the second batch. In contrast, it was possible to quantify 34 analytes in at least 80% of the urine specimens by iTRAQ^®-LC-MS/MS.

The higher TEs of iTRAQ^®-LC-MS/MS appear to be mainly due to excess of multiple reaction-monitoring transitions acquired in the third of the four predefined time windows. In the first, second, and fourth period, 3 (PSer, PEtN, Tau), 7 (Asn, Ser, Hyp, Gly, Gln, EtN, Asp), and 10 (Val, Nva, Met, Tyr, Hcy, Ile, Leu, Nle, Phe, Trp) amino acids are monitored, respectively. In contrast, in the third period 24 amino acids (Cit, Sar, bAla, Ala, Thr, Glu, His, 3MHis, 1MHis, Hcit, Asa, GABA, bAib, Abu, Aad, Ans, Car, Pro, Arg, Hyl, Orn, Cth, Cys, Lys) are monitored, with only half as many data points recorded. This has

a significant influence on the reproducibility of peak areas. For the second batch of urine specimens, mean ± SD of %TE (range) was 33.09±14.60 (18.21-73.31) for period 3, while it was (excluding methionine) 21.16±7.39 (13.88-40.64) for periods 1, 2, and 4. This shortcoming may be alleviated by recent implementation of scheduled sMRM that allow definition of as many overlapping periods as there are amino acids, with each amino acid monitored only for the time period of its expected elution from the column. For maximum precision, chromatographic resolution of amino acids will have to be improved to limit number of overlapping periods.

In conclusion, GC-MS and LC-MS/MS are attractive alternatives to the amino acid analyzer. The advantages of GC-MS are its complete automation, short runtime, and higher precision; its one limitation is the smaller number of amino acids amenable to analysis. In comparison, iTRAQ^®-LC-MS/MS excels in greater number of amino acids amenable to analysis and current availability of 42 stable isotope labeled standards. Incorporation of scheduled MRM, improved chromatographic resolution, and an advanced integration algorithm may improve reproducibility of the iTRAQ^® method.

7 Combined amino and fatty acid analysis by GC-MS

7.1 Introduction

An important sub-compartment of the metabolome are lipids and their comprehensive analysis is the subject of lipidomics.^{68, 69} Lipids can be categorized into several classes, including for example non-esterified fatty acids (NEFAs), triglycerides and phospholipids. Essentially all NEFAs in serum are bound to albumin.⁷⁰ Fatty acids are compound with a carboxyl group and an alkyl chain which is either saturated or unsaturated and differ in length. Most of the natural fatty acids have an even number of carbon atoms, usually 14, 16, 18 or 20 because their biosynthesis involves acetyl-CoA, a coenzyme carrying a two-carbon-atom group. The double bond can occur in a cis or trans configuration. In general, the fatty acids in biological systems contain only cis double bonds. The most common fatty acids in mammals are shown in Table 1.

Fatty acids, in particular stearic acid, oleic acid, linolenic acid and palmitic acid, are precursors for the synthesis of cholesterol and steroid hormones that regulate a wide range of functions, including blood pressure, blood clotting, blood lipid levels, immune and inflammatory responses to injury and infection.^71,

72 Several analytical methods have been developed for lipid analysis. Lipid extraction is commonly performed by Folch⁷³ or Bligh & Dyer extraction.⁷⁴ Another approach is the determination of the fatty acid composition by GC-FID or GC-MS after conversion into fatty acid methyl esters (FAMEs). Esterification is achieved using acidic methanol⁷⁵, iodomethane or BF3/methanol. To avoid lengthy sample preparation steps Lepage & Roy developed a method for the direct transesterification of all classes of lipids in plasma using an acetyl chloride/methanol mixture.⁷⁶ This method was further simplified by Masood et al. by introducing a one-step stock solution method, without the requirement for subsequent neutralization or centrifugation to separate phases.⁷⁷

Table16: Common natural fatty acids (saturated and unsaturated)

Common name of acid

Abbreviation Chemical structur

Saturated fatty acids

Myristic acid C14:0

HO O

Palmitic acid C16:0

HO O

Stearic acid C18:0

HO O

Unsaturated acid

Palmitoleic

acid C16:1

O

HO

Oleic acid C18:1

O HO

Linoleic acid C18:2

O HO

Arachidonic acid C20:4

O

HO

Docosahexanoic

acid C22:6

O HO

Husek et al. reported the applicapility of alkyl chloroformate derivatization to fatty acids.³⁷ Mateo-Castro et al. used ethyl chloroformate derivatization in aqueous medium to analyze amino, fatty and bile acids by GC-FID in binders used in artistic paintings after the samples were hydrolyzed by HCl.⁷⁸ Our aim was to integrate fatty acids in the fully automated quantitative method by GC-MS using propyl chloroformate derivatization to analyze amino acids and fatty

acids in the same analysis. The analysis of the fatty acids should allow either the analysis of free fatty acids, or the total fatty acids from all lipid classes. Due to the behavior of propyl chloroformate in base as a good esterifying reagent, the fatty acids that are attached to other molecules should react with the reagent immediately.

7.2 Materials and methods

7.2.1 Chemicals

The fatty acids C10:0, C12:0, C14:0, C16:1, C16:0, C18:1 cis, C18:0, C18:1 trans, C18: 2, C18:3, C20:0, C20:4, C22:1, C22:0, C22:6, C24:1, and C24:0 were purchased from Sigma. The [U-13C] fatty acid mix was from Medical Isotopes Inc. (Pelham, USA).

7.2.2 Biological samples

The applicability of the method was tested using human, mice and bovine serum. Human serum was collected from healthy volunteers. Bovine serum was provided by collaborators from the clinic for ruminants in the veterinary faculty of the Ludwig-Maximilians-University Munich (LMU). Mice serum was obtained from collaborators at the University of Regensburg. Due to low sample volume available from the latter, several samples were pooled to perform reproducibility studies. Twenty microliters of serum were always used.