NONTARGETED DISCOVERY OF XENOBIOTICS IN HUMAN URINE BY MALDI-TOF/TOF-MS
Dissertation Presented
by
Yuanyuan Yao
To
The Bouve’ Graduate School of Health Sciences in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Pharmaceutical Sciences with specialization in Biomedical Sciences
NORTHEASTERN UNIVERSITY BOSTON, MASSACHUSETTS
April 2018
ABSTRACT
In this dissertation research, nontargeted analysis of the urine metabolome, including xenobiotics, was studied using LC (Liquid Chromatography)-MALDI (Matrix Assisted Laser Desorption Ionization)
MS (Mass Spectrometry) techniques. MALDI is a sensitive soft ionization MS technique that has been mainly used to analyze large molecules such as peptides, proteins, and nucleic acids. Here, MALDI MS methods were employed for detection of urine metabolites. To increase the recovery of nonpolar metabolites, a novel porous extraction paddle (PEP) was validated with co-workers and used for urine extraction. A method for sample preparation including UHPLC (Ultra High-Performance Liquid
Chromatography) was optimized to facilitate detection of nonpolar urine sulfate metabolites by MALDI
MS. Using this approach, the detection coverage of such compounds was greatly expanded as compared to prior methods. Detection of 1129 MS precursor ions corresponding to putative sulfate and glucuronide metabolites was achieved. Combining MS and MS/MS experiments, a strategy was developed for tentative identification of the detected metabolites. This led to the first nontargeted analysis of environmental contaminants in urine. It was shown that the detection sensitivity of positive-mode MALDI MS can be enhanced using enzymatic deconjugation and cationic tagging methods. Also, an evaporative derivatization method was developed to increase the sensitivity of negative-mode MALDI MS for detection of phenolic compounds. Overall, through careful method development and optimization, the usefulness of LC-MALDI
MS as an analytical platform for the measurement of the urine nonpolar metabolome, including urinary xenobiotics, has been extended.
Northeastern University Bouvé College of Health Sciences
Dissertation Approval
Dissertation title: Nontargeted Discovery of Xenobiotics in Human Urine by MALDI- TOF/TOF-MS
Author: Yuanyuan Yao
Program: Doctor of Philosophy in Pharmaceutical Sciences with a Specialization in Pharmaceutics
Approval for thesis requirements for the Degree of Doctor of Philosophy in: Pharmaceutical Sciences
Dissertation Committee (Chair):
Signature: ______Date______Printed Name: ______
Other committee members:
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Associated Dean of Graduate Education, Bouvé College of Health Sciences:
Signature: ______Date______Printed Name: ______
ACKNOWLEDGEMENTS
Finishing the research and writing the dissertation has been an Odyssey for me. I want to thank my committee for their advices and patience. I appreciate having Dr. Giese as my mentor. He not only taught me about mass spectrometry but also showed me a role model to balance the multiple responsibilities in life. I would not be able to continue and finish my dissertation without Dr. Giese continuous support and encouragement. Also, I am indebted to Dr. Poguang Wang in our lab for his help throughout my research.
Dr. Wang always provide me kind guidance with his deep and broad knowledge of chemical analysis and led me through many obstacles in my research. Finally, I am grateful to my daughter and husband who inspired me to persist in overcoming difficulties in life.
TABLE OF CONTENTS
1. INTRODUCTION
1-1. The scope of dissertation work………………………………………………………………...1
1-2. Xenobiotics in urine………………………………………………………………...... 2
1-2.1. Human urine composition………………………………………………………………....2
1-2.2. Small molecules in urine: endogenous metabolites and xenobiotics…………………...... 3
1-2.3. Metabolism of xenobiotics……………………………………………………………...... 5
1-2.4. Possible correlations between xenobiotics and diseases………………………………...... 7
1-3. Analysis of urine xenobiotics………………………………………………………………...... 8
1-3.1. Metabolomics in general………………………………………………………………...... 8
1-3.2. Target and Nontargeted analysis .. ………………………………………………………. 9
1-3.3. Special aspects of urine xenobiotic analysis……………………………………………...11
1-3.4. Current development of xenobiotics analysis of urine……………………………………13
1-4. MS methods for chemical analysis of biological samples……………………………………15
1-4.1. A new analytical platform for urine metabolic analysis based on MALDI-TOF-MS…….15
1-4.2. Soft ionization techniques for MS spectrometry………………………………………….17
1-4.3. MS analyzers……………………………………………………………………………..24
1-4.4. Tandem MS………………………………………………………………………………29
1-4.5. Application of MS techniques in urine metabolomics……………………………………35
1-4.6. Use of MALDI for small molecule analysis……………………………………………...36
1-5. Sample preparation methods for MS analysis………………………………………………..37
1-5.1. Urine sample collection …………………………………………………………………37
1-5.2. Chemical derivatization of xenobiotics for MS analysis…………………………………39
1-5.3. Solid phase exaction of biological samples………………………………………………43
1-5.4. HPLC of complex biological samples for MS analysis………………………………….47
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2. MATERIALS AND METHODS
2-1. Evaporative derivatization reaction with sulfobenzoic anhydride……………………………48
2-2. Preparation of PEP bags for exaction of urine metabolites…………………………………49
2-3. Urine sample collections……………………………………………………………………...51
2-4. Direct MALDI-MS analysis of urine metabolites extracted by MP-PEP……………………...52
2-5. Optimized sample preparation method for UHPLC-MALDI MS analysis…………………... 53
2-6. HPLC and UHPLC ………………………………………………………………………….54
2-7. MALDI TOF MS and TOF/TOF tandem MS ………………………………………………. 55
2-8. Enzymatic deconjugation and cationic tagging of urine……………………………………... 56
3. RESULTS AND DISCUSSION
3-1. Evaporative derivatization of phenols with sulfobenzoic anhydride for negative-mode MALDI-
MS …………………………………………………………………………………………... 56
3-1.1. SBA evaporative derivatization reaction and MALDI MS analysis of a model phenol (4-
phenyl-phenol)……………………………………………………………………………… 57
3-1.2. Anionic Tagging and MALDI MS analysis of a 15-phenol mixture……………………...68
3-2. Development of Porous Extraction Paddle (PEP) for urine metabolite extraction………….73
3-2.1. The PEP with solid phase extraction adsorbents………………………………………….73
3-2.2. Evaluation of extraction efficiency of various PEP with a standard dye………………….75
3-2.3. PEP extraction of urine samples for qualitative analysis of metabolites………………… 76
3-2.4. PEP extraction of urine samples for quantitative analysis of targeted metabolites………..83
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3-3. Optimized procedure for UHPLC-MALDI MS analysis of urine metabolites………………..86
3-3.1. Our urine sample preparation strategy for LC/MALDI MS analysis……………………. 87
3-3.2. High reproducibility of our sample preparation strategy…………………………………89
3-4. UHPLC-MALDI analysis of sulfatome and glucuronidome of urine samples……………….91
3-4.1. UHPLC-UV spectra of 6 urine samples…………………………………………………. 91
3-4.2. Sulfatome and glucuronidome of six urine samples detected by UHPLC-MALDI MS… 94
3-4.3. Tentative assignment of the sulfate conjugates by matching METLIN database…………96
3-4.4. Examples of sulfated metabolites discovered in urine samples by MALDI MS MS/MS. 100
3-4.5. Candidate pollutants in the 6 urine samples……………………………………………. 104
3-5. Deconjugation and cationic tagging of urine samples for UHPLC-MALDI analysis………..107
3-5.1. Optimization of conditions for enzymatic deconjugation of urine …………………….108
3-5.2. Cationic tagging of the deconjugated urine sample…………………………………….. 111
3-5.3. UHPLC MALDI MS analysis of cationic tagged urine sample………………………… 113
3-5.4. MALDI-MS spectra of a cationic tagged deconjugated urine sample………………….. 115
4. SUMMARY AND CONCLUSSION…………… ………………………………………..117
5. PUBLICATIONS IN THIS STUDY………………………….…………………………. 118
6. REFERENCES……………………………………………………………………….… ...119
III
LIST OF TABLES
Table 1. Common conjugations of xenobiotics (denoted as X in the table) in the phase II metabolism….11
Table 2. Examples of matrix molecules for UV and IR MALDI……………………………………….…19
Table 3. Silylating and acylating reagents for chemical derivatization of acids, alcohols and amines for GC- MS…………………………………………………………………………………………………………32
Table 4. Cationic tagging reagents for positive mode LC-MS chemical analysis………………………….35
Table 5. Examples of ion exchange adsorbents…………………………………………………………….38
Table 6. Yield of solution phase derivatization reactions of 4-phenylphenol at different reaction conditions………………………………………………………………………………………………….54
Table 7. Yield of derivatization reaction in solid phase at room temperature at different time lengths. The reactants are from concentrating of 50-uL of 0.05M 4-phenylphenol, 0.5M SBA, and DMAP (2% w/w of 4-phenylphenol) …………………………………………………………………………………………..55
Table 8. Yield of solid phase derivatization reaction at different temperature for 2 hours. The reactants are from concentrating of 50-μL of 0.05M 4-phenylphenol, 0.5M SBA, and DMAP (2% w/w of 4- phenylphenol)……………………………………………………………………………………………..55
Table 9. Yield of solid phase derivatization reaction at 60°C for different time lengths. The reactants are from concentrating of 50-μL of 0.05M 4-phenylphenol, 0.5M SBA, and DMAP (2% w/w of 4- phenylphenol)……………………………………………………………………………………………..55
Table 10. Yield of the 4-phenylphenol : SBA, DMAP (2% w/w of 4-phenylphenol) solid phase derivatization reaction at 60 °C for 1 hour at different initial concentrations of the reactants in solution..56
Table 11. The 15 phenolic compounds in the mixture: 1) 4-nonylphenol; 2) 4-phenylphenol (4PP); 3) 2,4- dimethylphenol; 4) 4-chloro-3-methylphenol; 5) bisphenol A (BPA); 6) o-cresol; 7) phenol; 8) 2,4- dichlorophenol; 9) 2-nitrophenol; 10) 4-nitrophenol; 11) 2-methyl-4,6-dinitrophenol; 12) 2,4-dinitrophenol; 13) 2-chlorophenol; 14) 2,4,6-trichlorophenol; 15) pentachlorophenol. ND stands for “not readily detected”………………………………………………………………………………………………….. 61
Table 12. The yield of the SBA-tagging of pentachlorophenol at various temperature for 2 hours………...62
Table 13. The six adsorbents used to make the MP-PEP. All adsorbents were purchased from Supelco (Bellefante, PA, USA)……………………………………………………………………………………..65
IV
Table 14. The number of putative sulfate and glucuronide conjugated metabolites in the sixurine sample discovered by our UHPLC MALDI MS and MS/MS analysis…………………………………………….86
Table 15. The hits of pesticides, herbicides, and priority pollutants that may exist in the six urine samples discovered by searching METLIN as shown in Figure 38……………………………………………….....95
Table 16. Total MALDI MS intensities (x10-5) of urine sulfates…………………………………………..96
LIST OF FIGURES
Figure 1. The structures of the three most abundant molecular compounds in the dry mass of human urine...2
Figure 2. The metabolic pathway of catecholamines from phenylalanine. The acronyms represent the enzymes that catalyze the corresponding reactions: AADC (acromatic amino acid decarboxylase), AAAH (biopterin-dependent aromatic amino acid hydroxylases), COMT (catechol-O-methyltransferase), DBH (dopamine beta-hydroxylase), PNMT (phenylethanolamine N-methyltransferase)………………………...4
Figure 3. A schematic flow chart of the xenobiotic metabolism in human body……………………………5
Figure 4. Three examples of xenobiotics that have known or potential adverse effects on human health….6
Figure 5. Two ionic tagging reagents for derivatization of metabolites for negative mode MS………….35
Figure 6. The urine collection guidelines for participants of this study to collect urine samples at home…43
Figure 7. The weak anion exchange SPE cartridge used in our study……………………………………..45
Figure 8. An anionic tagging agent SBA: 2-sulfobensoic acid cyclic anhydride…………………………49
Figure 9. Derivatization of phenolic metabolites by SBA for subsequent MALDI-TOF-MS and MS/MS in negative ion mode…………………………………………………………………………………….……49
Figure 10. The MALDI (negative mode) MS spectra of the analyte sample of (A) unmodified 4- phenylphenol (~1ng/spot), and the control sample (B) the MALDI matrix, alpha-cyano-4-hydroxycinnamic acid (CCA). The spectrum of unmodified 4-phenylphenol sample is indistinguishable from that of control sample……………………………………………………………………………………………………..50
Figure 11. Derivation of 4-phenylphenol with SBA. ……………………………………………………..51
- Figure 12. MALDI (negative mode) MS spectra of (A) modified 4-phenylphenol (C19H13O5S ) (~0.2 nmol/spot) and (B) CCA matrix. ………………………………………………………………………….51
V
Figure 13. MALDI MS/MS spectra of the parent ion at m/z=353.05 for (A) modified 4-phenylphenol (C19H13O5S‒) (~0.2nmol/spot) and (B) pure CCA matrix. ………………………………………………52
Figure 14. Reverse phase HPLC chromatograms of the reaction mixture of 4-phenylphenol (4PP) SBA- tagging reaction. (A) solution-based reaction at 80 °C for 2 hours. (B) Evaporative reaction at 60 °C for 1 hour. Subsequent MALDI MS analysis showed peak 1 is SBA-4PP and peak 2 is underivatized 4PP……..53
Figure 15. Evaporative SBA tagging reaction for 4-phenylphenol. The picture shows the reaction mixture after evaporation in a SpeedVac. …………………………………………………………………………..54
Figure 16. MALDI (negative mode) MS spectra of (A) product of solid phase reaction with 5μL of 5x10- 6M 4-phenylphenol in initial solution, and (B) CCA matrix. ………………………………………………57
Figure 17. MALDI MS/MS spectra of the parent peak at m/z=353.05 for (A) the product of solid phase reaction with 10-6M phenylphenol in initial solution, and (B) CCA matrix………………………………...58
Figure 18. A scheme of general SBA-tagging reaction of phenolic compounds for MALDI MS and MS/MS analysis. R represents the apo-phenol moiety of phenolic compound……………………………………...59
Figure 19. Negative mode MALDI MS spectra of (A) a mixture of 15 phenolic compounds in Table 11 derivatized by evaporative SBA tagging reaction; phenylphenol in initial solution, and (B) the reaction blank without phenol mixture..…………………………………………………………………………….60
Figure 20. HPLC chromatography of the SBA tagging reaction mixture for pentachlorophenol at 100 °C for 2 hours. Peak 1 and 2 are the SBA-tagged pentachlorophenol and the underivatized pentachlorophenol, respectively...……………………………………………………………………………………………...62
Figure 21. The porous extraction paddle (PEP) having the following components from top to bottom: stirring motor; four off-sets (vertical white rods), black lid (for a 0.5 gallon jar, not shown); shaft; horizontal PTFE bar into which the shaft is press-fitted at the top of the bar, with a slot on the lower side that accommodates the cage, and with two vertical slots for two Tiewraps; porous nylon bag (6.0 × 6.5 cm) containing 2 g of MP-adsorbent that is sandwiched between two sheets of stainless steel mesh (each 8.0 × 8.7 cm), where the meshes are held together further with three additional Tiewraps………………………65
Figure 22. The structure of Malachite Green dye…………………………………………………………..66
Figure 23. A vial containing Malachite Green dye with a mini-PEP at (A) time = 0 and (B) time = 8 minutes after shaking at 230 oscillation rate. .………………………………………………………………………66
Figure 24. Absorbance of Malachite Green dye in a 4% acetic acid solution during extraction using a PEP packed with (A) an Empore SDB-XC membrane , (B) 2.0-g MP-adsorbent (n =3), (C) 2.0-g Carboxen-1003 adsorbent. .………………………………………………………………………………………………...66
VI
Figure 25. MALDI MS spectra of (A) eluates from urine-exposed PEP, and (B) CCA matrix blank. The insets are the low-mass region of the spectra zoomed in 25 times to show the low intensity peaks………...68
Figure 26. The MALDI MS/MS spectrum of the m/z = 525.030 peak in the MS spectrum. The accurate mass of precursor ion and the pattern of product ions match a sulfate, glucuronide double conjugate of apigenin/genistein.………………………………………………………………………………………...69
Figure 27. The MALDI MS/MS spectrum of the m/z = 169.035 peak in the MS spectrum. The accurate mass of precursor ion and the pattern of product ions match uric acid. ………………………………...... 70
Figure 28. The MALDI MS/MS spectrum of the m/z = 265.110 peak in the MS spectrum. The accurate mass of precursor ion and the pattern of product ions match vitamin B1. ………………………………....71
Figure 29. The MALDI MS/MS spectrum of the m/z = 358.264 peak in the MS spectrum. The accurate mass of precursor ion and the pattern of product ions match 2,3-dioctanoylglyceramide………………….72
Figure 30. (A) The MALDI MS/MS spectrum of the m/z = 1734 peak in the MS spectrum. The accurate mass of precursor ion and the pattern of product ions match a peptide with sequence AKVGEAKVMIIIDSME, which is derived from kinesin light chain. (B) The peptide sequence was annoted using the DeNovo Explorer software. ………………………………...... 73
Figure 31. The three compounds used to spike the urine sample for evaluating MP-PEP extraction and MALDI MS analysis. ………………………………...... 74
Figure 32. The MALDI MS spectra of the PEP-extracted urine samples (A) spiked with 400-nmol of each thiamine-d3, O-octanyl[N-methyl-d3] carnitine, and reserpine; (B) similarly spiked sample as (A) but with additional 140-fmol of the three compounds added to each spot on the MALDI sample plate. The labeled peaks are assigned to: 1, thiamine; 2, thiamine-d3; 3, O-octanoly carnitine; 4, O-octanyl[N-methyl-d3] carnitine; 5, nonanoyl carnitine; 6, decatrienoyl carnitine; 7,9, decenoly cartnitine; 8, decanoly carnitine. The inset is the nonspiked urine. ………………………………...... 75
Figure 33. The MALDI MS spectra of the PEP-extracted urine samples (A) spiked with 400-nmol of each thiamine-d3, O-octanyl[N-methyl-d3] carnitine, and reserpine; (B) similarly spiked sample as (A) but with additional 140-fmol of the three compounds added to each spot on the MALDI sample plate; (C) nonspiked. The peaks m/z = 609.280, 610.285, and 611.289 are respectively assigned to protonated reserpine and two isotopic reserpine. ……………………………….………………………………………………………...76
Figure 34. The workflow of our analysis of urine sulfateome. ………………………………...... 78
Figure 35. UHPLC chromatograms of three successive injection of the urine sample E. The chromatograms are shifted vertically for clear comparison. ………………………………...... 81
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Figure 36. UHPLC chromatograms of the urine sample E prepared by the step 1-5 in Figure 34 at time 0 (curve 1) and 6 weeks later (curve 2. The chromatograms are shifted vertically for clear comparison……..81
Figure 37. UHPLC chromatograms at 260 nm, 214 nm and 320nm of six urine sample prepared by the sample preparation step 1-5 in Figure 52. ……………………………………………………………...... 83
Figure 38. Evaluation of the 1129 precursor ions detected in the UHPLC-MALDI MS analysis of the sixurine sample. The putative identity of the precursor ions was determined by searching their experimental exact masses in the metabolite database METLIN. Marched compounds are designated as “hit”…………87
Figure 39. The molecular backbone of steroids and flavonoids. ………………………………...... 89
Figure 40. Detection of morphine-3-sulfate by the UHPLC-MALDI analysis. (a) Detection of the precursor ion as M‒1 at m/z = 364.086 with accuracy of 3 ppm (indicated by the blue arrow) in MALDI MS spectrum. (b) Detection and assignment of the two product ions of putative morphine-3-sulfate (m/z = 80 and 284) in the MALDI MS/MS spectrum…………..………………………………...... 91
Figure 41. Detection of 3β,16α-dihydroxyandrostenone sulfate by the UHPLC-MALDI analysis. (a) Detection of the precursor ion as M‒1 at m/z = 383.151 with accuracy of 5 ppm (indicated by the blue arrow) in MALDI MS spectrum. (b) Detection and assignment of the three product ions of 3β,16α- dihydroxyandrostenone sulfate (m/z = 80, 97 and 303) in the MALDI MS/MS spectrum………………….92
Figure 42. Detection of estriol-3-sulfate-16-glucuronide by the UHPLC-MALDI analysis. (a) Detection of the precursor ion as M‒1 at m/z = 543.151 with accuracy of 5 ppm (indicated by the blue arrow) in MALDI MS spectrum. (b) Detection and assignment of the three product ions of estriol-3-sulfate-16-glucuronide (m/z = 80, 463 and 367) in the MALDI MS/MS spectrum…………………………………………………93
Figure 43. The phthalate pollutants that match the MS ions of the urine samples in our study……………96
Figure 44. 4-sulfatase from human. X-ray structure from Protein Data Bank in Europe (PDBe: 1fsu). Sulfatase catalyzes hydrolysis of sulfate ester into sulfate and phenol or alcohol………………………....97
Figure 45. The relative intensity of 11 sulfate peaks detected by MALDI MS for the urine samples before and after enzymatic deconjugation reactions under different conditions. Control is the original urine sample prepared by the same procedure but without adding the enzyme………………………………………….99
Figure 46. The yield of deconjugation of the 11 sulfate conjugates under different reaction conditions measured by MALDI MS………………………………………………………………………………...100
Figure 47. Cationic tagging of various types of analytes using CAX-B…………………………………101
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Figure 48. The schematic work flow of deconjugation and cationic tagging of urine sample for UHPLC MALDI MS analysis. ………………………………...... 102
Figure 49. The UHPLC chromatograms of the cationic tagged urine sample (black trace) and the control of blank tagging reaction mixture without urine (blue trace). UV absorbance was monitored at 260 nm…..103
Figure 50. MALDI MS spectrum of the UHPLC elute fraction at 42 minutes of the cationic tagged urine sample and the control of blank tagging reaction mixture. ………………………………...... 104
Figure 51. MALDI MS spectra of the unmodified urine sample and the cationic tagged urine sample. The amount of cationic tagged urine sample loaded for MS experiment is 1/120 of that used for native urine experiment. The red arrows indicate the sulfated testosterone/prasterone/dehydroepiandrosterone detected in the native urine sample and the cationic tagged molecule of the same metabolite in the modified urine sample. The inset is the MS/MS spectrum of the precursor ion (m/z = 492.348)………………………….105
IX
1. INTRODUCTION
1-1. Scope of the dissertation work
My dissertation research is focused on developing new techniques to advance the usefulness of
MALDI-TOF/TOF-MS for non-targeted discovery of xenobiotics in urine. Analysis of small molecule components of biological fluid samples, such as urine, finds important applications in disease diagnostics, pharmaceutical studies, as well as environmental research. Due to the complexity and diversity of the chemical composition of urine samples, urine analysis presents a challenge of ever-increasing needs of novel techniques for detecting newly emerged drugs or environmental pollutants at a broad range of concentration levels.
The background knowledge needed to understand this work is reviewed. In section 1-2, I provide an overview of xenobiotics, i.e. foreign small molecules lacking purpose in the body, in urine. Three questions are answered in section 1-2: What kinds of small molecules are commonly found in human urine samples? How they are metabolized in the body and find their way into urine? And what is the relationship between xenobiotics and diseases? In section 1-3, I give the reader a short review on the general background and current methods and techniques for chemical analysis of urine xenobiotics. One of the most widely used types of techniques in the analytical toolbox of xenobiotics is the combination of chromatography and mass spectrometry. Section 1-4 gives the reader with general scientific background a more detailed introduction to the MALDI-TOF-MS technique. In section 1-5, some sample preparation strategies for MS analysis are reviewed.
In my research, I developed several specific sample preparation techniques. In section 3-1, I present a novel evaporative derivatization method to add an anionic tag to phenols for the negative-mode detection by MALDI. To lay down a basis for urine metabolomic analysis, I describe in section 3-2 a novel porous extraction paddle (PEP) for urine extraction. Section 3-3 describes an optimized sample preparation protocol of a sequential extraction and separation method. I have shown that this protocol can be used to
Page 1 of 133 prepare urine samples for MALDI-TOF-MS analysis, and the results are highly reproducible. Using this protocol, I have demonstrated that MALDI-TOF-MS can be used to discover tentatively xenobiotics in urine samples. Specifically, UHPLC-MALDI analysis of the nonpolar sulfatome of six urine samples is described in the section 3-4. Finally, I present in section 3-5 a novel method of deconjugation and cationic tagging of urine samples for UHPLC-MALDI analysis in the positive mode.
1-2. Xenobiotics in urine.
1-2.1. Human urine composition
In the animal kingdom, most species including mammals, birds and reptiles remove the water soluble metabolic wastes from blood stream through the excretory system. Humans generate urine in kidneys as a result of sequential processes of filtration, tubular reabsorption, and tubular secretion. Urine is excreted through ureter, urinary bladder, and urethra to outside of body. The urine is essentially an aqueous solution of metabolic by-products. A healthy person produces 0.6 to 2.5 liters urine each day.(1) 91 to 96% weight of urine is water.(2) The average dry weight of the urine of a person in a day is about 60 grams.(2)
The dry weight of urine contains between 65% and 85% organic compounds, as well inorganic salts for the rest.(2) Urination is the main pathway for human to eliminate nitrogen-containing wastes from the blood stream. On average, one liter urine have 8.12 grams of nitrogen element, 8.25 grams of oxygen, 6.87 grams
Urea Creatinine Uric Acid Figure 1. The structures of the three most abundant molecular compounds in the dry mass of human urine.
Page 2 of 133 of carbon, 1.51 grams of hydrogen, 1.87 grams of chloride, 1.17 grams of sodium and 0.75 grams of potassium.(2) Due to the high nitrogen content, urine was once used as a nitrogen source for production of gunpowder in the 19th century.(3) The most abundant organic compounds in the dry weight of urine is urea
(~9.3 g/L), creatinine (~0.67 g/L) and uric acid (~0.25-0.75 g/L) (Figure 1). Other organic materials in urine, including endogenous metabolites, xenobiotic metabolites and sometimes proteins, usually exist at much lower concentrations. Urine is normally sterile before reaching the urethra, where anaerobic Gram-negative bacteria break down urea into ammonia that gives the odors of urine.
1-2.2. Small molecules in urine: endogenous metabolites and xenobiotics
Most molecules in urine are the metabolic byproducts in the processes of producing energy needed to support the life, as well as the molecular building blocks of living organisms, e.g. lipids, carbohydrates, amino acids, and nucleotides. These endogenous metabolites play important physiological roles, such as hormones, neurotransmitters, etc. The biological pathways of the metabolite synthesis usually consist of a series of interconnected enzyme-catalyzed chemical reactions, involving many structurally related intermediate metabolites. For example(4, 5), Figure 2 shows the metabolic pathway for synthesis of catecholamine hormones from phenylalanine. The endogenous metabolites and the secondary metabolites produced along the metabolic pathways can get into the blood circulation and be degraded by enzymes such as monoamine oxidase (MAOs). Many endogenous metabolites and their degraded forms can be found in urine.
Besides the nutrients and the small molecules having physiological functions, there could be also
“foreign” chemicals in human body, e.g., drugs and pollutants. The molecules that are neither produced by human body nor from normal food and lack purpose in the body, are called xenobiotics. Despite the general definition, the term xenobiotic is most often used to refer to the chemicals having known/potential adverse effects on normal physiological functions of human body. Common xenobiotics include environmental pollutants, pesticides, herbicides, and food additives. Elevated level of pollutants in environment due to
Page 3 of 133 human activity raises an increasing issue to environment and healthcare. For example, some polycyclic aromatic hydrocarbons (PAHs) from burning fossil fuels are carcinogens. Metabolically activated PAHs can bind to DNA to form DNA adducts and cause cancers.(6) Exposure to PAHs are also associated with
AADC PNMT
L-Phenylalanine Phenethylamine N-Methylphenethylamine
AAAH N-Methyltyramine PNMT AADC
DBH L-Tyrosine p-Tyramine
AAAH p-Octopamine
PNMT AADC
L-Dopa Dopamine COMT Synephrine
PNMT
Epinephrine Norepinephrine 3-Methoxyltyramine (Adrenaline) (Noradrenaline) Figure 2. The metabolic pathway of catecholamines from phenylalanine. The acronyms represent the enzymes that catalyze the corresponding reactions: AADC (acromatic amino acid decarboxylase), AAAH (biopterin- dependent aromatic amino acid hydroxylases), COMT (catechol-O-methyltransferase), DBH (dopamine beta- hydroxylase), PNMT (phenylethanolamine N-methyltransferase).
Page 4 of 133 cardiovascular diseases as well as developmental disorders.(7) Generally, the human body degrades xenobiotics in the liver and excretes them mainly into urine.
1-2.3. Metabolism of xenobiotics
The human body can detoxify xenobiotics through metabolic pathways consisting of a series of enzyme-catalyzed chemical modifications. The dynamic concentrations and duration of xenobiotics in human body is limited by the rate of metabolism. The in-vivo chemical transformation of xenobiotics take place in multiple organs, mainly in liver and kidney. The detoxification of xenobiotics is generally accomplished through two sequential phases. Phase I of xenobiotic metabolism involves a variety of enzymatic reactions to introduce polar and reactive functional groups to the otherwise inert lipophilic xenobiotic molecules. These modified molecules are then chemically conjugated to hydrophilic or ionic molecules in the phase II metabolism. Finally, the xenobiotic conjugates produced in phase II could be
Lipophilic Xenobiotic oxidation reduction hydrolysis Phase I
Reactive Intermediates
Electrophiles Nucleophiles
glutathione sulfation glucuronidation Phase II conjugation acetylation
Hydrophilic/Ionic Conjugates
Figure 3. A schematic flow chart of the xenobiotic metabolism in human body.
Page 5 of 133 further modified, excreted from cells, and removed from body in urine. A schematic flow chart of xenobiotic metabolism is shown in Figure 3.
Due to the diversity of metabolic pathways for each xenobiotic, there are usually many modified and conjugated forms of the original molecule present in urine at different levels. For instance, metabolomics studies have revealed 24 derivatives of nicotine in human urine of the individuals who smoke.(5) Therefore, identification and quantification of xenobiotics should take into account the unmodified molecules as well as their derivatives.
1-2.4. Possible correlations between xenobiotics and diseases
By definition, xenobiotic molecules are “foreign” to living organisms and have no purpose there.
Some xenobiotics may be benign and not interfere with normal physiological functions. More often than not, xenobiotics can cause health issues at high levels and for long exposure. Most familiar examples include (Figure 4): the historically used pesticide, dichlorodiphenyltrichloroethane (DDT), which is carcinogenic; the controversial plastic component, bisphenol A (BPA), which is said to be endocrine- disrupting; the plasticizers, phthalates, which are believed to be associated with high risk of breast cancer, birth defects, as well as endocrine disruption and obesity in children.
phthalates DDT BPA
Figure 4. Three examples of xenobiotics that have known or potential adverse effects on human health.
Besides the adverse effects on health of adults, even more serious concerns are the birth defects and early age developmental defects. Recent studies have found high abundance of xenobiotics metabolites,
Page 6 of 133 especially endocrine-disrupting compounds such as bisphenol A, phytoestrogens, and polychlorinated biphenyls, in the amniotic fluid of women with high risk of preterm birth.(8, 9)
As an ever-increasing volume of studies establishes the relationship between xenobiotics and human diseases, chemical analysis of biological samples, e.g., blood, urine, cerebrospinal fluids, may prove to be valuable tools for disease diagnostics or risk evaluation. Indeed, measurement of xenobiotics and, more generally, metabolomics represent a new trend for personalized medicine.(10)
1-3. Analysis of urine xenobiotics
1-3.1. Metabolomics in general
The studies of “omics” refer to multi-analyte analysis of biological molecules in a sample. Analysis of DNA, mRNA and proteins of biological milieu has led to the development of genomics, transcriptomics, and proteomics, respectively.(11-13) Knowledge of the detailed profiles of bio-macromolecules have greatly advanced the research in biology, medicine, and pharmaceutical science. Nevertheless, the central dogma of biology does not depict the complete landscape of biochemistry of living organisms. Small molecules are ubiquitous in vivo and play diverse essential functions such as energy sources, structural units, hormones, enzyme cofactors and substrates. Therefore, identification and quantification of small molecule metabolites in various types of samples are crucial to reconstruct a holistic picture of the metabolic pathways associated with disease and physiological functions. The complete set of small molecule metabolites of a biological specimen is called its metabolome. The study of metabolome is referred to as metabolomics.
In metabolomics, the analytes are usually small molecules with mass lower than 1500 Daltons.
These small molecules in biological samples include common metabolites (e.g., amino acids, sugars, lipids, phenols, steroids, and alkaloids) and the xenobiotics which are specific to individuals.(14, 15) Because small molecule metabolites in body are constantly synthesized, adsorbed, modified, and degraded, the metabolome is intrinsically dynamic. The identity and concentrations of the small molecules in a
Page 7 of 133 metabolome depend on many factors, including the types of biological samples, the time of sample collection, the age, diet, and health condition of the individual. Even though the metabolome of a tissue or a biological fluid can change rapidly, metabolomics analysis provides “snapshots” of molecular footprints of metabolic reactions. Since metabolites are directly related to the phenotypes, metabolomics is especially suitable for disease diagnostics and evaluating the effects of diets, drugs, pollutants, or medical treatments on individual’s health. Indeed, personalized metabolomics is an essential component of the personalized medicine.(16)
1-3.2. Target and Nontargeted analysis
In general, analysis of metabolites can be classified as targeted or non-targeted. The goal of targeted analysis is to quantify known metabolites in biological samples. The behavior of the target metabolite in the experiment, e.g., the retention time in a HPLC measurement or fragment masses produced in a tandem
MS experiment, is known from the literature, database, or the measurement of a standard sample. The metabolite of interest in the biological samples is identified by observing the same behavior as the standard in the experiments. Typically, a couple of orthogonal experimental techniques, i.e., methods with very different selectivity, are used to analyze the same sample to increase the confidence of identification. For example, target metabolite analysis can be conducted using a LC-MS-MS method.(17) In this method, the molecules in a liquid sample are separated by their retention time on a liquid chromatography column. The
LC fractions are ionized in a mass spectrometer (usually by a soft ionization method) to produce the precursor ions for each molecule. The m/z (mass-to-charge ratio) of the precursor ions are determined by the first mass analyzer. Then, a precursor ion with selected m/z will be fragmented in the collision cell of the MS spectrometer. The m/z of the fragments are determined by the second mass analyzer. The LC-
MS/MS provides three orthogonal properties of the target molecule: interaction (LC retention time), molecular weight (m/z of the precursor ion), and structural clues (m/z of the fragments). A commonly used method based on the specific fragmentation reaction is called Selected Reaction Monitoring (SRM).(18)
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Using an isotopic analogue of the target metabolite as internal standard, SRM MS usually can be used to accurately quantify the concentration of a metabolite in the target analysis.(19)
In nontargeted metabonomic analysis, the goal is to discover all metabolites or all metabolites of the same type in the metabolome of a biological sample.(20, 21) Because no prior knowledge about the analytes is known and the sample preparation is not optimized for a specific metabolite, nontargeted analysis usually is less sensitive and much less quantitative than targeted analysis. However, the metabolites identified in nontargeted analysis can be further quantified in targeted analysis.(22) In addition, the metabolic profiles of biological samples obtained in the nontargeted analysis can be used to compare different groups of samples, e.g., patients with a disease and the healthy individuals. The differentiation of sample groups is achieved by statistical analysis of the metabolite profiles. A variety of statistical tools, including univariate and multivariate methods, can be used for non-targeted metabonomic analysis.(23-25) The univariate methods, such as t-test and Analysis of Variance (ANOVA), are based on comparison between the values of an individual parameter (metabolite) of the sample groups.(26, 27) These methods are most suitable to differentiate the large sample groups having substantial difference in one metabolite signal. Some multivariate methods include Multivariate Analysis of Variance (MANOVA), ANOVA Simultaneous
Component Analysis (ASCA), Principle Component Analysis (PCA), and Partial Least Squares Regression
(PLS).(28-31) The multivariate approach is often less intuitive than the univariate approach. However, when there is no single metabolite showing substantial difference between the sample groups, multivariate methods can be used to discover small variations of multiple metabolites that collectively differentiate the sample groups. In addition, multivariate methods can reveal the correlation between metabolites which may shed light on the associated metabolic pathways.(32)
1-3.3. Special aspects of urine xenobiotic analysis
Metabolomics, especially of xenobiotics, of human urine samples potentially have a broad range of applications in medical diagnostics, nutrition study, pathology, pharmacology.(33-36) Xenobiotics, such as
Page 9 of 133 environmental pollutants and chemical residuals from household products, are in part metabolized and excreted in urine.(37, 38) The chemical composition of urine is complicated due to the complexity of metabolomic pathways. A xenobiotic molecule may yield multiple intermediate and end products of metabolism.
Most of the chemicals in urine are water soluble compounds present at very low concentration. The xenobiotics in urine often have functional groups defined by the enzymatic conjugation reactions in the phase II of metabolism. Common metabolic conjugations include glucuronidation, sulfate conjugation, glutathione (GSH) conjugation, amino-acid conjugation, acetylation, and methylation (Table 1). These conjugations change the molecular weight, ionic state, lipophilicity, and acidity of the xenobiotic molecules.
In some metabolomics analysis, the characteristic conjugate functional groups help to separate and differentiate the metabolites.(21) In other cases, enzymatic de-conjugation reactions are conducted in the samples to enhance separation selectivity and simplify the complexity of their chemical profile.(39, 40) For examples, the metabolites of phthalates and phthalate derivatives in urine samples were tested by a method based on enzymatic deconjugation of sample, solid-phase extraction, and reverse phase HPLC-MS-MS.(40)
Conjugation Conjugate group MW pKa Enzyme Substrate change range groups of X (g/mol) Glucuronidation 176 3.0-3.5 UDP-glucuronosyl- -OH, -NH, - transferases COOH (UGTs)
Sulfate 80 <1 Sulfotransferases -OH, -NH
Glutathione 289 2.1, 3.5 Glutathione S- electrophiles transferases
Glycine 57 3.5-4.0 glycine- -COOH, - aminotransferase NOH,
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Methylation 14 --- Methyltransferases -OH, -NH, - SH, metals N-acetylation 42 --- N-acetyltransferase -NH
Table 1. Common conjugations of xenobiotics (denoted as X in the table) in the phase II metabolism.
1-3.4. Current development of xenobiotics analysis of urine.
The chemical composition of urine is difficult to characterize due to its complexity. Researchers have been conducting detailed chemical analysis of urine for over a century, and only with the technical advancements since 1960 have then been able to provide a metabolic profile of human urine (41-43). For the nontargeted analysis of urine, currently it is not possible to measure (identify, quantify, or classify) the entire range of metabolites by a single analytical method. Various kinds of metabolic profiling platforms have been applied to maximize the metabolite coverage. The most common analytical techniques used for nontargeted metabolic analysis of human urine are nuclear magnetic resonance (NMR) spectroscopy (44-46) and mass spectrometry (47, 48). Separation techniques such as gas chromatography (GC) and liquid chromatography (LC) are often coupled to the MS to facilitate the analysis of metabolites.
Each of the techniques has its advantages and limitations. NMR can handle complex metabolite mixtures. NMR measurements require minimal sample preparation and thus can be made rapidly (a few minutes per sample for urine) (49). Also, NMR is unbiased, robust, and reproducible. Since NMR is a nondestructive method, the samples can be further tested using other techniques to identify specific metabolites. Furthermore, NMR experiments can provide quantitative and detailed structural information about small organic molecules. Nontargeted metabolic profiling studies using NMR have been carried out
(46, 50-53) and by far, up to 209 compounds were identified in human urine in one study (53). On the other hand, NMR spectroscopy has a relatively low sensitivity (lower limit of detection is about 1 µM).
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In contrast, mass spectrometry (MS) has high sensitivity (the detection limit routinely can be as low as a few femtomoles). MS techniques also have high selectivity, high resolution, wide dynamic range, and high robustness. The MS-based analysis such as gas chromatography coupled with mass spectrometry
(GC-MS) (54-56) and liquid chromatography coupled with mass spectrometry (LC-MS) (57-62) are commonly used for urine analysis. GC-MS is performed using a capillary chromatographic column for separation and the electron impact (EI) or chemical ionization (CI) MS for detection. GC-MS has very high resolution, good sensitivity, but variable robustness. Also, the readily available commercial databases for GC-MS are very helpful in the identification of some of the metabolites. Studies have been done for the nontargeted analysis of urine using GC-MS since 1970s (53, 63-72), and up to 294 compounds were claimed to be identified in human urine in one study (66). However, the analytes in the urine need to be stable at high temperatures in order to be analyzed by GC-MS (73). Another major limitation of GC-MS technique is that it is not suitable for nonvolatile compounds. Many classes of polar biochemical compounds (such as sugars, nucleosides, and amino acids) are nonvolatile, and thereby cannot be directly analyzed. Chemical derivatization allows some nonvolatile compounds to be analyzed by GC-MS. Nevertheless, the by-products introduced by derivatization can cause artifacts and the extra sample preparation steps can introduce additional variability and analyte losses.
To complement GC-MS and increase metabolite coverage in the nontargeted chemical analysis of urine, LC-MS can be used. LC-MS is usually done with a reversed-phase liquid chromatographic column coupled with an electrospray ionization (ESI) mass spectrometer for online analysis. ESI, a soft ionization
MS technique, can detect nonvolatile and ionic compounds with high sensitivity. A common problem occurs with LC-MS, namely “ion suppression” effect, in which coeluting compounds change the ionization of other analytes and thus signals are suppressed. Nontargeted urine studies using LC-MS have been carried out (74-77) and by far, up to 258 metabolites were claimed to be identified in human urine in one study (76).
Other MS techniques such as inductively coupled plasma MS (ICP-MS) have also been used for nontargeted urinary trace elemental composition of urine (53, 78), and up to 40 urinary trace metals or minerals were
Page 12 of 133 identified in human urine in one study (53). Combinations of two or more platforms have also been applied by many researchers to increase the metabolite coverage (79-81). Although overlap occurs in the metabolite detection, the methods are complementary to each other.
The collection of all the metabolites (organic compounds below 1.5 kDa) in human urine is called the human urine metabolome. In 2013, scientists at the University of Alberta, Canada, reported the first draft of the human urine metabolome (53). So far, the Urine Metabolome Database (UMDB) contains a total of 2651 confirmed urine metabolites, which is a complete list of all possible metabolites that have been detected in human urine using current technologies in a targeted or nontargeted way. The urine metabolite identification and quantification are far from complete. The number of metabolites in the UMDB is expected to increase. Profiling the urine metabolome of an individual patient is anticipated to become a powerful diagnostic tool in medicine. To increase the coverage of globular (non-target) urine metabolite analysis, it is important to develop new methods that complement the traditional metabolite profiling techniques.
1-4. MS methods for chemical analysis of biological samples
1-4.1 A new analytical platform for urine metabolic analysis based on MALDI-TOF-MS
In my study, I explored the use of a new platform for nontargeted analysis of metabolites in human urine. This platform is based on the matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) along with MALDI-TOF/TOF-MS combined offline with ultra- performance liquid chromatography (UHPLC).
MALDI-MS has advantages such as high sensitivity, high mass accuracy, high throughput and tolerance to contamination and buffers. Like ESI, MALDI is a soft ionization method and is suitable for nonvolatile and fragile analytes. Furthermore, MALDI usually produce singly charged molecular ions.
Therefore, the spectra of MALDI-MS are simple and easy to interpret. In MALDI-MS, the samples can be
Page 13 of 133 stored and revisited if needed. MALDI-TOF/TOF-MS is powerful at structural elucidation and sometimes isomer discrimination and can further aid in the metabolite identification.
MALDI-TOF-MS has been widely used for analyzing large biomolecules such as proteins and nucleotides, but much less so for low molecular mass compounds due to matrix ion interference, detector saturation and quantitative irreproducibility. Nevertheless, MALDI-MS has the potential to contribute to the human urine metabolome studies. Indeed, Sun et al. studied the negatively charged water soluble cellular metabolites from murine myocardium using MALDI-TOF/TOF-MS and identified 285 metabolites based on mass accuracy and 90 metabolites were confirmed by tandem MS analyses (82). The studies showed that MALDI MS is a promising tool in small molecule metabolite profiling.
In my study, I further employed sample preparation methods, including sample derivatization and solid-phase extraction (SPE) separation, followed by UHPLC-MALDI-MS analysis. UHPLC has high resolution and thus can help MS in reducing analyte interferences and ion suppression. The analytical method developed in my study can detect trace constituents in the complex human urine, including the metabolites that are not currently in the UMDB. Also, our platform has the potential to be adapted for the analyses of other biofluids such as human cerebrospinal fluid, saliva, or serum. Importantly, the advances in sample preparation we made in this project can benefit all relevant MS techniques for nontargeted chemical analysis of biofluids.
1-4.2 Soft ionization techniques for MS spectrometry
Mass spectrometer determines the mass-to-charge ratio of the ions derived from the analyte molecules. Thus, the first component of a MS spectrometer is the ionization module which turns the analyte molecules into ions. Since J. J. Thomson first used MS spectrometry to determine the isotopes of Ne atom in early 20th century,(83) many ionization technologies have been developed. In the history of MS spectrometry for chemical analysis, electron impact (EI) and fast atom bombardment (FAB) ionization have
Page 14 of 133 been widely used. Today, EI ionization is still popular for GC-MS systems.(84) EI uses an electron beam generated from a heated filament in electric field to impact the evaporated sample molecules in vacuum. EI ionization produces the ions of the fragments of the analyte molecule. Hence, it is only suitable for volatile molecules in samples with simple composition. For typical biological liquid samples, such as urine, blood, and cerebrospinal fluid, EI spectra may be too complicated to interpret.
Most modern MS spectrometers employ “soft” ionization methods which generate the intact molecular ions instead of fragments. Soft ionization significantly simplifies the MS spectra and thus are suitable for analysis of large biological molecules and complex samples. Common soft ionization techniques including electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), and matrix-assisted laser desorption ionization (MALDI).(85)
In ESI MS, the sample is prepared in volatile solvent, such as acetonitrile or methanol, and sprayed from a small nozzle into a capillary to form fine solution droplets. A coaxial sheath flow of N2 gas is used to facilitate the electrospray (often called nebulization). High voltage (~2-6 kV) is applied at the two ends of the ionization capillary. Thus, the sprayed droplets carry charges whose polarity is determined by the polarity of the voltage. As the charged droplets travel, the solvent gradually evaporates. When the size of droplet decreases to a critical size called Raleigh limit, the electrostatic repulsion between the like charges becomes greater than the surface tension of droplets. As a result, the droplets explode into many smaller droplets. This process is called Coulomb fission. As the solvent further evaporates, the small droplets become unstable and undergo further Coulomb fission. Finally, the charged analyte molecules in gas phase enter the MS analyzer.
In a positive mode ESI, the molecular ions are [M+zH]z+ or [M+Na]+. In a negative mode, the ions are [M–zH]z–.(86) ESI is a widely used MS spectrometry because it can be easily coupled with HPLC. It can be used to analyze both small molecules with a molar mass smaller than 500 Da, and large biological molecules like proteins and nucleic acids. For a large molecule, ESI often produces molecular ions (or quasimolecular ions) containing multiple charges at different atoms in the analyte molecule. The multiple charge peaks can complicate spectrum interpretation. On other hand, multiple-charge molecular ions also
Page 15 of 133 give ESI unique advantages over other MS techniques. First, ESI can readily determine molar mass of large molecules. For example, an antibody with molar mass 150 kDa usually produces in ESI molecular ions with between 50 to 70 charges, corresponding to mass-to-charge ratio, m/z, between 2000 to 3000.(87) The moderate m/z of the large protein falls into the typical detection range of MS analyzers. A second advantage of having a series of multiple-charge peaks of the same molecule is that simultaneously fitting of the multiple peaks (called deconvolution of spectra) improve the accuracy of the calculated molar mass.
For a small molecule ESI spectrum often gives single-charged peak which may be straight forward to interpret. The number of charges can be estimated by examine the 13C isotope peak that has slightly higher m/z than the most abundant base peak. The isotope peak of a single-charge ion has m/z 1Da higher than the base peak, while that of an ion with Z charges has m/z only 1/Z Da higher than the base peak. Not only ionic molecules but also nonionic molecules can be analyzed by ESI MS. For example, nonionic
+ + (88, 89) surfactants have been studied by monitoring the adduct ions such as [M+NH4 ] and [M+Na ].
Nonionic molecules with nucleophilic groups can form protonated ions [M+H]+ in the positive mode of
+ ESI. Formation of adduct with ammonium cation [M+NH4] is usually more efficient than protonation.
Moreover, for large molecules like proteins, adduct formation with ammonium and acetate ions can reduce formation of metal adducts and significantly simplify the ESI spectra. Ammonium acetate salt is often used in ESI solvent for the above reason and for its role in the HPLC separation and its volatility in the ion source.
Due to all these advantages, ESI is one of the most popular ionization technique in modern MS spectrometry. However, ESI also has its limitations. ESI is not suitable for analyzing nonpolar molecules.
Nonpolar molecules cannot be efficiently ionized by ESI. Also, ESI requires polar solvents, such as water, methanol, and acetonitrile, in which the nonpolar molecules have low solubility. For LC-MS analysis of less polar molecules, another soft ionization method called atmospheric pressure chemical ionization (APCI) is more suitable. The first step of APCI is similar to that of ESI. The solution, usually from HPLC, is
(90, 91) nebulized into a mist of fine droplets in a sheath flow of N2 gas. Instead of charging and breaking the droplets in a high electric field like ESI, APCI uses a heater at 350 to 500 °C to evaporate the solvent. The gas mixture of analytes, solvent and N2 enters the ionization chamber where the molecules are ionized by
Page 16 of 133 a corona discharge needle electrode. The voltage between the discharge needle and the outlet counter electrode is typically 2-3 kV. Corona discharging effectively ionizes the N2 which in turn transfer the charge to analyte and solvent molecules through gas phase chemical reactions.
APCI is an API where ionization occurs in the gas phase, while ESI is an API where ionization occurs in solution phase. Because APCI occurs in gas phase, solvent selection of LC-APCI MS is not limited by their conductivity and pH. Without the constraint of choosing solvents, APCI is a more versatile than ESI for LC-MS applications. APCI is widely used for analyzing polar and less polar small molecules with molar mass lower than 1500 Da.(92) However, APCI is not suitable for large molecules and thermally labile molecules because heating is used to convert the sample to gas phase. Another advantage of APCI over ESI is that it suffers less ion suppression. Ion suppression is the reduction of analyte signal response in MS due to the presence of ion suppressing impurities.(93) The ion suppressing species in samples often can be removed by isolation and separation methods. However, for complicated biological samples like urine, ion suppression problem may remain after separation by LC. APCI is generally less prone to ion suppression than ESI.
Another common soft ionization technique is matrix-assisted laser desorption ionization (MALDI).
The ionization mechanism of MALDI is very different from ESI and APCI. To prepare the samples for
MALDI analysis, the analytes are mixed with a large amount of so-called matrix molecules in volatile solvents, typically acetonitrile, ethanol, and water. Then, a drop of solution is spotted on a MALDI sample plate made of steel and allowed to dry by itself. As the solvent evaporates, the analyte and matrix molecules will co-crystallize into matrix crystals in which the analyte molecules uniformly embedded.(94)
In a MALDI instrument, a laser beam is directed to the crystalline sample spot to thermally ablate the top ~100nm part of the sample.(95) Since the diameter of laser beam is usually much smaller than sample spot, the laser typically scans over the sample spot many times to obtain an average result. Common lasers used in commercial MALDI instruments include UV and IR lasers: nitrogen laser (337 nm), Nd:YAG laser
(355 nm), Nd:YAG laser (266 nm), Nd:YAG laser (1-4 μm), and CO2 laser (10.6 μm). The matrix molecules are selected so that they have strong absorbance at the UV or IR wavelength of the laser.(96) Some common
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MALDI matrix compounds are listed in Table 2. Typical matrix for UV MALDI has conjugated double bonds that absorb photons with UV wavelength.(97) To allow efficient ablation when heated by the laser, the matrix molecules are usually not too big. On the other hand, they are not too small so that do not evaporate as the solvent of the spotted sample droplet dries. After ablation, the gas phase contains both matrix ions and the molecular ions of analyte. Typical analyte ions are [M+H]+, [M+Na]+, [M+nH]n+,
[M−H]−, and [M−nH]n−. The abundance of single and multiple charged molecular ions depends on the properties of analyte, matrix, laser intensity, and voltage. Compared to ESI and APCI, MALDI produces much less multiple-charged ions and thus simpler spectra for large molecules.(98)
The exact ionization mechanism of MALDI is still under debate. One theory suggests that the ionization of analyte occurs in the ablated gas through proton transfer reactions. In this model, the matrix molecules absorb the laser photons and convert the energy to both thermal energy and electronic energy, which result in ablation of sample and formation of matrix ion pairs [Ma+H]+ and [Ma−H]−.(99-101) Then, protons transfer between the matrix ions and the analyte molecules to produce analyte molecular ions
[M+H]+ and [M−H]−. Another model postulates that the ions of analyte are formed in the solution phase.
After ablated into the gas phase, some of the molecular ions are neutralized by counter-ions and photon- electrons, while the others retain their charge states. Hence, this mechanism is called “lucky survivor” model.(102, 103) Emerging experimental evidences suggest that both the gas-phase proton transfer model and the lucky survivor model contribute to the MALDI ionization of analytes.(104, 105) The gas-phase proton transfer process is favored when the laser intensity is high and proton affinity of matrix is low. The lucky survivor mechanism is more significant when the analyte structure favors formation of stable ions in solution.
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Name Structural Formula Molar Mass Wavelength Solvent (Da) (nm) 2,5-dihydroxy benzoic acid 154.12 337, Acetonitrile, (DHB, gentisic acid) 355, Water, 266, Methanol, 3k Acetone, Chloroform 3,5-dimethoxy-4- 224.21 337, Acetonitrile, hydroxycinnamic acid 355, Water, (SA, sinapinic acid) 266 Acetone, Chloroform
3-methoxy-4- 194.18 337, Acetonitrile, hydroxycinnamic acid 355, Water, (ferulic acid) 266 Propanol
α-cyano-4-hydroxycinnamic 189.17 337, Acetonitrile, acid 355, Water, (CHCA, HCCA) 3k Ethanol, Acetone,
Picolinic acid 123.11 266 Ethanol (PA)
3-hydroxy picolinic acid 139.11 337, Ethanol (HPA) 355, 3k
Glycerol (liquid matrix) 92.09 10k Water
Water ice 18.02 3-10k Water
Table 2. Examples of matrix molecules for UV and IR MALDI.
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Unlike ESI and APCI, MALDI cannot be directly coupled to HPLC to perform online LC-MS analysis. However, the eluted fractions of HPLC can be spotted on the MALDI sample plate that is preloaded with matrix solution. Alternatively, the matrix solution can be added after the eluted solution droplets dried on the plate. The sample plate so prepared can be stored and used many times for MALDI experiments since each measurement only consumes a very small volume of sample. Besides the advantage of allowing storage and repeated experiments, MALDI is also compatible with more LC solvent conditions than ESI and APCI. Because of its unique ionization mechanism, MALDI can be used to analyze ionic, polar, and nonpolar molecules using both polar and nonpolar solvents.(106, 107) MALDI is less sensitive than
ESI to solution conditions such as pH, salts, and Ion suppression.(108) Also, salts in the MALDI sample matrix can be removed by sample preparation such as solid-phase extraction or by directly washing the co- crystals on the sample plate with water. Another advantage of MALDI is its high sensitivity. MS sensitivity directly depends on the efficiency of ionization. The ionization efficiency of MALDI can be tuned by selecting different matrix, optimizing co-crystallization conditions, laser intensity, and voltage. Typically,
~5% ionization of analyte by MALDI can be achieved at favorable conditions. On contrary, high flow-rate
LC-ESI often has ionization efficiency less than 1%.(85) Also, the whole sample spot on a MALDI sample plate can be utilized for an experiment. Thus, MALDI-MS sometimes has higher sensitivity than regular
ESI-MS. The nanospray ESI technology has sensitivity comparable to that of MALDI. Detection of attomole (10–18 mole) amount of analyte have been reported for both MALDI and nanospray ESI MS.(109,
110)
As discussed before, it is essential to use multiple analytical platforms with different selectivity for urine metabolomics study, so that the detection coverage of metabolites is maximized. Using the instrument available in our lab, I employed MALDI-MS in my study to urine metabolome profiling. The high sensitivity of MALDI and its unique ionization mechanism can increase coverage of urine metabolome.
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1-4.3 MS analyzers
Once the sample molecules are ionized, their mass-to-charge ratio need to be determined by a MS analyzer. There are six common MS analyzers in commercial MS spectrometers, including quadrupole, magnetic/electrostatic sector, time-of-flight, quadrupole ion trap, ion cyclotron resonance, and Orbitrap.
Mass analyzers separate ions from an ion mixture and determine their mass-to-charge ratio, m/z. The basic physical principle of all mass analyzers is the same, i.e., the ions with different m/z will have different trajectory or pattern of motion in a given electric field, E, and/or magnetic field, B. The mechanic equations apply here are Newton’s second law, = , where a is the acceleration, and the Lorentz force law, =
+ × , where v is the velocity of ions. Despite the common physical principle, different MS analyzers have very different instrumental implementation and are suitable for very different applications.
To select one MS analyzer that fits the MALDI-MS study of urine metabolome, we need to reflect on the advantages and limitations of these MS analyzers.
Quadrupole MS analyzer consists of quadrupole rod electrodes with DC and RF electric potential.
For a given potential, only ions with selected m/z can pass through the quadrupole rod while the other ions are filtered out.(111) Quadrupole is the most popular analyzer for GC-MS and LC-MS due to its relatively low cost, small size of instrument, and easy extension to tandem MS applications with triple quadrupole.
In magnetic sector MS analyzers, the ions are first accelerated by an electric potential V to reach a kinetic
energy, = , and then fly into a magnetic sector where the ions travel at a speed v in a circular
trajectory with radius r. The centripetal force on the ions is = . Thus, the m/z of the ions is given
by = , i.e., the ions with different m/z can be selected by the radius of their circular trajectory. In most commercial sector MS spectrometer (so called double focusing sector analyzer), the magnetic sector is coupled with an electrostatic sector which further select ions by their kinetic energy to increase the resolution. Sector analyzers were the first MS analyzers that have been developed and commercialized.
They have very good resolution and quantitative reproducibility.(112) However, their use has been declining due to their large size, high cost, and difficult extension to tandem MS applications. Quadrupole and
Page 21 of 133 magnetic sector analyzers are m/z filters. They only allow ions with one m/z pass and be detected at a time.
To obtain the whole MS spectrum, the analyzers need to scan different m/z by varying the frequency of electric potential or the strength of magnetic field. This scanning work mode makes quadrupole and magnetic sector analyzers not suitable for MALDI-MS, because MALDI produces brief pulses of ions, rather than a continuous ion stream.
In contrast to the ion filter analyzers, another type of MS analyzers is the ion trap including quadrupole ion trap, ion cyclotron resonance (ICR), and Orbitrap analyzers. Quadrupole ion trap analyzer
(a.k.a. 3D ion trap) is made of two parabolic half-ring electrodes and two end cap electrodes. An RF AC electric potential is applied between the parabolic electrodes to trap the ions. The ions are moving between the electrodes in a sigmoid circle like a figure “8”. Ions with specific m/z can be selectively ejected to the detector by varying the frequency of electric potential. Quadrupole ion traps are widely used due to their compact size and high sensitivity.(113) But they tend to suffer from low resolution (~2,000), low mass accuracy (100-1000 ppm), small dynamic range, and lack of well-defined kinetic energy of ions for tandem
MS experiments. A variant of quadrupole ion trap is called linear ion trap (LIT). It uses quadrupole electrodes instead of parabolic electrodes to trap ions radially. LIT has a higher resolution (~30,000) than a 3D ion trap, but still limited mass range (< 4000 m/z).
Another popular ion trap analyzer is ICR analyzer in which ions are traveling in circular trajectory in a magnetic field (114). By simply equaling the centripetal force and the Lorentz force, = ,
one can determine the angular velocity of the ions, = . Thus, the m/z of ions can be calculated from their angular velocity. Most modern ICR instruments have a Fourier Transform detector (FT-ICR). The FT-
ICR detector is essentially a proximity ion sensor. Instead of directly detecting the ions hitting the surface of the detector, FT-ICR’s receiver plates measure the change of electric potential due to the movement of all ions in the trap. The time-domain signal is then converted to the frequency-domain signal by Fourier
Transformation. In this way, the angular velocity of all ions is determined simultaneously without ejecting ions. Due to the non-destructive detection mode of FT-ICR, ions can be stored and readily applied to tandem
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MS applications. FT-ICR can have very high resolution (~1,000,000) in a favorable case, but a relatively small dynamic range. The most recently commercialized MS instrument is the Orbitrap MS (115). In the
Orbitrap, the ions are trapped in an electric field between a central spindle electrode and a cylindrical outer electrode. The trapped ions orbit around the central electrode and harmonically oscillate along the axial direction. Ion detection in Orbitrap is achieved by determine the angular frequency of axial harmonic oscillation in a similar manner to FT-ICR. The Orbitrap analyzer has high resolution (~150,000), high mass accuracy (2 ppm), high sensitivity, good dynamic range, and good storage time of the trapped ions. However, both Orbitrap and FT-ICR MS spectrometers are expensive and require high vacuum.
Despite all the advantages of the high-resolution ion trap MS (FT-ICR and Orbitrap), the high price limits their accessibility to the majority research labs. Another MS analyzer called time-of-flight (TOF) is more affordable than FT-ICR and Orbitrap, but still well suitable for MALDI MS and tandem MS.(116) In a
TOF, the ions are accelerated in by an electric potential V to gain kinetic energy, = , and then let freely drift in vacuum tube with length of L to the detector. The ions with different m/z are differentiated
by their time of fight, = = . The TOF analyzer can also operate in a mode called reflectron TOF.
The reflectron is a set of plate electrode (ion mirrors) producing an electric field which reflects the ions.
The reflectron TOF not only has longer time-of-flight, but also helps to reduce the kinetic energy distribution of the ions. Ions can leave the acceleration field with slightly different initial kinetic energy which causes dispersion of the flight time and lower resolution. In reflectron TOF, the ions with higher kinetic energy will penetrate deeper in the reflector field and thus be delayed. The reflected ions with different kinetic energy will more likely arrive at the detector at the same time. Therefore, reflectron TOF has higher resolutions than the linear TOF. TOF MS is the fastest MS analyzer (20,000 scans/s). It is well suited to the pulse ion source from MALDI and tandem MS experiments. It is very sensitive due to the high ion transmission. Also, the mass range of TOF is the highest amongst all MS analyzers (practically up to
1,000,000 m/z. theoretically unlimited). TOFs also have high mass accuracy (10-100 pm) and high
Page 23 of 133 resolution (typically up to 50,000 for higher masses). These advantages make TOF analyzer a good choice for MALDI-MS study of urine metabolome.
1-4.4 Tandem MS
Using MALDI-TOF MS, one can determine the accurate mass of the molecular ions of the urine metabolites. By searching the accurate masses in metabolite database such as METLIN, NIST, and UMDB, the tentative identity of metabolites can be speculated. However, more structural information is needed to differentiate molecules with the same mass including the isomers, and ultimately identify the metabolites.
Tandem MS spectrometry provides a way to further investigate the structure of the metabolite molecules.
Tandem MS is also called MS/MS or MS2. In tandem MS, the selected precursor ions (e.g., the molecular ions) from the initial MS spectrum are deliberately broken into fragments. The product ions from the fragmentation are then analyzed to generate a MS spectrum of the fragments, which can shed light into the structure of the selected precursor ions. Using the fragment MS spectra, one can use database or software to deduce the structure of the analyte molecules to refine identification.(117) Some MS spectrometers, especially the ion trap instruments, can conduct higher order tandem MS experiments, MSn, with n larger than 3, which may allow the structure of fragments to be further elucidated.(118) Tandem MS increases the ability of MS spectrometry to identify unknown molecules.
The central step of tandem MS analysis is fragmentation of the molecules. Some fragment ions can be generated during the ionization process, especially in the “hard” ionization methods such as electron impact (EI) ionization. Besides the in-source fragment ions, some metastable ions with high internal energy can also be produced during ionization and will break into fragment ions before they reach the detector.
Sometimes, the in-source fragment ions and metastable ions can be used for single MS analysis of structure, but are not desirable for tandem MS.(119, 120) In tandem MS experiments, the fragment ions are generated in a more controlled way. There are a few fragmentation methods (ion activation methods) used for tandem
MS, namely, collision-induced dissociation, surface-induced dissociation, photodissociation, electron- induced dissociation, etc.(121) All these various fragmentation methods use different mechanisms to achieve
Page 24 of 133 the same goal, i.e., to increase the internal energy of the molecular ions so that chemical bonds will break after a short period of time.(121)
One of the most common fragmentation method is collision-induced dissociation (CID).(122) In a
CID cell of MS spectrometers, the precursor ion is accelerated by an electric potential and enters a chamber filled with a neutral gas where the ions and neutral molecules collide. Due to collisions, part of the kinetic energy of the precursor ion will be converted into excess internal energy which results in spontaneous bond breaking. Considering an inelastic collision between a precursor ion (mass M1, kinetic energy, K) and a still
neutral molecule (mass M2), the kinetic energy loss after collision will be . Thus, the maximum
excess internal energy can be generated by collision is . According to this expression, higher initial kinetic energy of ion and heavier neutral molecules produce higher excess energy and more fragmentation.
Since the excess internal energy could also cause fragmentation and/or ionization of the neutral molecule, noble gases are usually used as the neutral target gas to minimize such fragmentation and ionization. In practice, CID can be categorized into high-energy collision and low-energy collision.(123, 124) For high- energy collision, the precursor ions are accelerated to above 1000 eV, and the collision produces broadly distributed high excess internal energy. Thus, high-energy collision can generates many possible fragments of a labile precursor ion giving an information-rich tandem MS spectrum (125). Due to the high initial kinetic energy, a heavy target molecule is not required for high-energy collision. Helium is commonly used because of its relatively low price, high ionization energy, and low scattering of ions. Moreover, since the high- energy CID spectra already contain peaks for many possible fragments, the spectra are usually highly reproducible and is independent of CID conditions, i.e., the initial kinetic energy of precursor ions, target gas, pressure, and temperature of the gas. On contrary, low-energy CID of the precursor ions with kinetic energy lower than 100 eV produces an incomplete set of fragment ions.(125) The low-energy CID spectra are often less reproducible and sensitive to collision conditions. Large noble gas elements like Xeon and
Argon are often used for low-energy CID to increase the excess internal energy. Both initial kinetic energy and pressure of the target gas have strong effects on the low-energy CID tandem MS spectra. Low pressure
Page 25 of 133 of target gas is preferred to reduce multiple collision which leads to randomization of excess internal energy and possible rearrangement of the precursor ions.
Other ion activation methods use different mechanisms to increase internal energy of the precursor ions and cause spontaneously decay. Surface-induced dissociation (SID) uses a solid surface instead of gas as the collision target.(126, 127) Photodissociation (PID) is an efficient ion activation method for the ions with a UV chromophore group.(128) These ions can absorb the UV photons that have enough energy for breaking chemical bonds. Sometimes, two-photon excitation happens breaking bonds with higher energy than one photon. Two-photon excitation of ions and decay of the excited ions in vacuum is more probable than that in solution phase, because the ions are not cooled down by interactions with solvent molecules. PID has high selectivity of ion activation and is especially suitable for the ion trap MS spectrometers which give the ions more time to absorb photons.(129) Electron-capture/transfer dissociations occur when positive ions interact with an electron beam (ECD) or when negative ions interact with a cationic reagent such as anthracene and azobezm (ETD).(130) The fragmentation of ECD increases as the current of electron beam increases.(131) Amongst the variety of ion activation techniques, CID is the most versatile and well- established one. In my research, the tandem MS analysis was conducted using CID.
Tandem MS instrumentation has been implemented in different ways. In most tandem MS spectrometers, the precursor ions and the product ions are analyzed in two separate MS analyzers: one before the ion dissociation cell and one after it. This setup is called “tandem-in-space” MS/MS.(132)
Common combinations of MS analyzers include: triple quadrupole (QqQ, the first and the third quadrupole,
Q, are analyzers, the middle one, q, is a RF collision quadrupole), quadrupole and TOF (QTOF), TOF/TOF, four-sector (BE/BE, B is magnetic sector, E is electric sector, BE is a double-focusing sector analyzer),
BE/TOF, BE/Q, BE/ion-trap), etc.(133) Moreover, “tandem-in-time” MS can be conducted with an ion trap
MS analyzer, in which the precursor and the product ions are separated at different time.(134) In tandem-in- time MS experiment, more than two stages of fragmentation, MSn, can be conducted.(135) The tandem MS experiments in my project were conducted using TOF/TOF MS tandem-in-space analyzer.(136)
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There are four main types of tandem-in-space MS experiments: product ion scanning, precursor ion scanning, constant neutral loss scanning, and selected reaction monitoring.(137) Product ion scanning generates a spectrum of the product ions from fragmentation of the selected precursor ion and thereby can help to elucidate the molecular structure of the precursor.(138) When we want to find out the molecules belonging to a specific class of compounds that produce a characteristic fragment ion, precursor ion scanning experiments can be very useful. The precursor ions are scanned and dissociated one at a time to determine those precursors which produce the selected product ion in the second MS analyzer.(139) Another way to detect the molecules of a specific class is the constant neutral loss MS analysis. Instead of looking for a characteristic fragment ion, neutral loss MS simultaneously scans the m/z of precursor ions and product ions at a fixed mass difference ∆m/z. The neutral loss of mass during fragmentation is used as a benchmark for detecting the molecules of the class of interest.(140) Selected reaction monitoring (SRM) is widely used in targeted chemical analysis. SRM fixes the m/z of both precursor and product ions to take advantage of a known fragmentation reaction. SRM greatly increases the selectivity and sensitivity of the analysis of the targeted molecule. A similar type of experiment, multiple reaction monitoring (MRM), is useful in multiple targeted analysis.(141) In MRM experiments, a series of selective fragmentation reactions are monitored for detecting multiple molecules of interest. Each cycle of MRM searches for one specific pair of precursor and product ions. The four types of tandem MS experiments should be chosen for the specific application based on the purpose of application and a priori knowledge about the analyte of interest.
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1-4.5 Application of MS techniques in urine metabolomics
Due to the high sensitivity, selectivity, and structural analysis versatility of MS spectrometry, it has been widely used in combination with chromatographic techniques for urine metabolomics studies. In general, the MS method is well suited for global discovery of unknown metabolites while quantification usually requires using internal standards chemically similar to the analytes.(142) One profound endeavor is to use LC-MS urine analysis for discovery of biomarker for diagnosis and prognosis of diseases. Five nucleosides (N-2-methylguanosine, 3-methyluridine, 6-methyladenosine, inosine, and N,N- dimethylguanosine) in urine samples were analyzed by HPLC-ESI-QqQ-MS as potential biomarkers for urogenital cancer. (143) In another study, urine metabolome of renal cell carcinoma (RCC) patients was analyzed by UHPLC-ESI-LTQ-MS and GC-EI-MS. Three metabolites including 4-hydroxylbenzoate, gentisate, and quinolinate were discovered as diagnostic biomarkers for RCC.(144) In a study of jaundice syndrome in patients with liver disease, the urine samples were analyzed by UHPLC-ESI-QTOF-MS. The urine metabolome of patients was differentiated from that of the control group of healthy individuals by 44 metabolites.(145) Another study of the children had cardiopulmonary bypass surgery using UHPLC-ESI-
QTOF found that the patients with rapid elevation of homovanillic acid sulfate in urine after surgery have significant high risk to develop the complication of acute renal injury.(146) Interestingly, MS-based metabolic profiling has been used to study a rat model of depression. The urine metabolome of the rats under chronic unpredictable mild stresses and that of a group of healthy rats have been examined by
UHPLC-ESI-QqQ-MS in both positive and negative ionization modes. The depression group and the control group were well separated by PCA analysis of the MS spectra.(147) As briefly reviewed above, MS- based urine metabolomic profiling is useful in the field of medical research. However, most previous studies employed LC-ESI and GC-EI MS. Since the MS ionization methods have very different selectivity for analytes, it is desirable to introduce other MS platforms for detection of urine metabolites. Each MS technique has its own advantages and limitations, and the work flow of urine metabolomic analysis needs to be optimized by considering the characteristics of the MS method to be used.
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1-4.6 Use of MALDI for small molecule analysis
The conventional wisdom of MS spectrometry tells us that MALDI MS is designed for analyzing large molecules like proteins but not suited to measure small molecule metabolites. The application of
MALDI MS to study molecules smaller than 500 Da is limited by several factors, e.g., interference from matrix molecules, saturation of detector in the low molecular weight range, difficulty to couple with HPLC, and low reproducibility for quantitative analysis.(148) A continuous research endeavor has been made to demonstrate that these technical obstacles of small molecule analysis using MALDI can be circumvented.(149-156) Indeed, MALDI has been used to analyze a variety of small molecules, including small peptides, carbohydrates, quaternary ammonium salts, sterols, nucleosides, purine and pyrimidine bases, amino acids, surfactants, opioids, retinoids, catecholamines, antibiotics, prostaglandins, metal complex of porphyrins, phthalocyanines, prodrugs, and drug metabolites. (149-156)
In fact, the main reason which limits popularity of MALDI MS in small molecule applications comes from the competition of ESI and APCI MS. Admittedly, ESI and APCI MS spectrometry are intrinsically suitable for analyzing small molecules. However, MALDI MS has its own advantages such as high sensitivity and unique ionization mechanism. As discussed before, nontargeted analysis of urine metabolome requires use of multiple analytical platforms with high sensitivity but different selectivity to maximize the metabolite detection. From this perspective, MALDI MS provides a valuable alternative to the conventional methods such as NMR, ESI, and APCI MS. In addition, modern TOF MS analyzers have high resolution, rapid experimental run, and large dynamic range. These features of TOF analyzer could rectify the traditional limitations of MALDI for small molecule analysis. Moreover, automated MALDI plate spotters allow coupling with HPLC and collection of LC fractions directly on MALDI sample plates.(157) In my study, I will demonstrate that MALDI-TOF is indeed a useful tool for nontargeted analysis of part of urine metabolome.
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1-5. Sample preparation methods for MS analysis
To apply MALDI-TOF MS for urine metabolomic analysis, proper sample preparation is essential.
Typical sample preparation processes include molecule enrichment, derivatization, and separation. A good sample preparation procedure can significantly improve the HPLC separation, increase the sensitivity and selectivity of MS analysis, simplify the MS spectra, and reduce detector saturation. Potentially, a good sample preparation can greatly facilitate analysis of the urine samples that contain many metabolites at very low concentration. Enrichment of molecules from the urine samples increases the concentration of metabolites. Urine metabolites can be selectively derivatized to separate and identify them by functional groups. Separation of urine metabolites before HPLC-MS analysis can markedly reduce the detector saturation and simply the MS spectra. Therefore, one of the focus of my study is to make optimized sample preparation procedures for HPLC-MALDI MS analysis of urine metabolome.
1-5.1 Urine sample collection
Urine specimen plays an irreplaceable role in clinical diagnostics, medical and pharmaceutical research.(158-160) Various methods have been established to collect and store urine samples.(161) These methods differ by the time and device of collection. Urine samples are often collected by patients using a urine sample jar at a chosen time. A first-morning-urine specimen is often taken for urinalysis and microscopic analysis since it is relatively concentrated. A midstream-clean-catch specimen is suitable for microbiological culture and antibiotic diagnostics due to low cellular contamination. A time-collection specimen is collected at different time, typically with an interval of 8 or 24 hours, for monitoring change of urine chemicals over time. A collected specimen is often used for pediatric urinalysis and microscopic analysis. Urine samples can also be collected by doctors using a catheter, or directly taken from bladder using a syringe (so called suprapubic aspiration.
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All the methods described above are used to collect urine in its original liquid form. The urine samples need to be stored before analysis. Typically, urine samples are stored in refrigerator with certain preservatives.(162-165) Common preservatives include hydrochloric acid, boric acid, acetic acid, tartaric acid, sodium propionate thymol, chlorhexidine, ethyl paraben, and toluene. However, the conventional urine sampling methods suffer from two disadvantages. First, the volume of urine samples is limited and thus not suitable for analysis of low abundance chemicals. Second, large urine samples are not easy to store and ship. This requires the chemical analysis being conducted near the site of sample collection, and thus greatly limits the subject groups that can be studied in medical and research applications.
To search for a solution to the problem of urine sample long-term storage and transport, it is helpful to revisit the techniques that have been developed for the biological and environmental samples in liquid form. One interesting approach is to use the adsorbent bags to adsorb and enrich the chemicals from the liquid or gas samples to the solid particles. Polyester bags containing solid phase extraction particles such as Amberite XAD2 (hydrophobic crosslinked copolymer of styrene and divinylbenzene) or Oasis HLB
(polymer of the hydrophilic N-vinylpyrrolidone and the hydrophobic divinylbenzene) have been used for sampling environmental waters.(166) Mulberry paper bags containing Tenax TA (poly 2,6-diphenylphenol) particles proved to be useful for adsorb essential oil compounds from rose and lavender (167) Fiberglass bags containing activated carbons have been used to extract dyes from environmental water samples.
Cyclohexane solvent in dense polypropylene membrane bags have been used to extract triazines, organochlorine and organophosphorus compounds from a variety of environmental and food liquid samples.(168) Small-pore (0.2 μm) polypropylene bags containing C18 adsorbent particles have been used to extract carbamate pesticides from soil suspension samples.(169) Inspired by these adsorbent bag techniques, we developed a multi-adsorbent bag for extraction and enrichment of chemicals in urine samples.
1-5.2 Chemical derivatization of xenobiotics for MS analysis
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Chemical derivatization of biological samples is often conducted to convert groups of metabolites into the derivatives that are more suitable for the chromatographic and MS analysis. The common types of subsequent analysis after chemical derivatization are GC-MS, LC-MS in a positive mode, and LC-MS in a negative mode.(170)
Many polar or ionic metabolites are nonvolatile and thus cannot be analyzed by GC-MS.
Conventionally, chemical derivatization is used to convert these nonvolatile metabolites into volatile molecules. For example, organic acids, alcohols, and amines can react with silylating reagents and acylating reagents to form derivatives with reduced polarity. (Table 3) (171, 172) The derivatized molecules can then be measured by GC-MS, and the molecular structures may be partly deduced from the fragment peaks.
Silylating reagents Acylating reagents CMDMSDEA PFPOH (chloromethyl)dimethyl 2,2,3,3,3-pentafluoro-1- silyldiethylamine propanol
TMSDEA HFBI trimethylsilyldiethylamine N-heptafluorobutyryl
imidazole
BSTFA TFAA N,O- trifluoroacetic anhydride bis(trimethylsilyl)trifluoroacetami de
TMSI MBTFA (trimethylsilyl)imidazole N-methyl- bis(trifluoroacetamide)
HMDS PFPA hexamethyldisilazane pentafluoropropionic anhydride MSTFA N-methyl-N- (trimethylsilyl)trifluoroacetamide TMCS trimethylochlorosilane
MTBSTFA N-tert-butyldimethylsilyl-N- methyltrifluoroacetamide
Table 3. Silylating and acylating reagents for chemical derivatization of acids, alcohols and amines for GC-MS.165
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With the development of sensitive modern LC-MS technologies, polar metabolites can be analyzed with LC coupled with soft ionization MS to produce simple spectra. LC-MS also enables tandem MS experiments to further elucidate molecular structure. However, some molecules are poorly ionized with typical LC-MS techniques, such as ESI and MALDI. To address this issue, ion tagging chemical derivatization can be employed to enhance the MS signal response and/or introduce isotopes to the analyte molecules. For positive mode MS, cationic tagging reagents are used to add positive charges to the neutral or negatively charged molecules by reacting usually with hydroxyl, carboxyl, carbonyl, and amine groups.
Numerous cationic MS tags have been developed to increase the sensitivity and selectivity of positive mode
LC-ESI and MALDI MS analysis of alcohols, carbohydrates, fatty acids, lipids, sterol, peptides, etc. (Table
4) (173-186)
3- N,N-diethyl-1,4- (dimethylamino)- butanediamine 1- propylamine (tag –COOH) 173 (tag –COOH)173 N,N-diisopropyl- N,N,N-trimethyl- 1,5- 1,4-butanediamine pentanediamine (tag –COOH) 173 (tag –COOH) 173 4-(2- 4-(2- O aminoethyl)pyridi aminoethyl)morphol
ne ine (tag –OH, – N (tag –COOH) 173 COOH) 173 H2N Hydroxylamines dansylhydrazine (tag aldehydes, (tag aldehydes, ketones) 174 ketones) 174
asymmetric dansyl chloride 174 dimethylethylened (tag –NH2, –NH–) iamine (tag –COOH) 174
o- 1-DAPAP phenylenediamine (S)-1-(4-
(tag –NH2, –NH–) dimethylaminophen 174 ylcarbonyl)-3- aminopyrrolidine (enantiomeric tag – COOH) 175
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3-DAPAP DMG (S)-3-(4- N,N- dimethylaminophe dimethylglycine nylcarbonylamino (tag oxysterol) 176 )-pyrrolidine (enantiomeric tag –COOH) 175 Isoniconylinoyl Picolinoyl chloride chloride (tag (tag hydroxylsteroid) 177 hydroxylsteroid) 177
Niconylinoyl d0/d5-pyridine chloride (isotopic tag (tag hydroxylsteroid, hydroxylsteroid) carbohydrate) 178 177
Phenyl-GPN GP (tag glycans) 179 Girard’s reagent P (tag glycans) 179
GPN Phenyl-GP Phenylacetic (tag glycans) 179 hydrazide (tag glycans) 179 AMPP TMPP N-(4- Tris(trimethoxy- aminomethylphen phenyl) yl)pyridinium phosphonium 180 (tag glycans) (tag –COOH, –NH2) 181
2-Fluoro-1- (4-Chlorocarbonyl- methylpyridinium phenyl)-trimethyl- p-toluenesulfonate ammonium iodide (tag –OH) 182 (tag –OH) 183
Triethyl-(4- 2-(2- hydrazinocarbonyl (triethylamino)ethox -benzyl)- y)-2- ammonium iodide phenylethaneisothio (tag aldehydes, cyanate iodide 183 183 ketones) (tag –NH2)
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(2-(2-(2-Bromo- TMPP-Ac-OSu acetylamino)-1- tris(2,4,6- phenyl-ethoxy)- trimethoxyphenyl)ph ethyl)-triethyl- osphonium acetic ammonium iodide acid N- (tag –COOH) 183 hydroxysuccinimide ester 184, 185 (tag –NH2) TSH p- toluenesulfonylhy drazine (tag aldehydes, ketones) 186
Table 4. Cationic tagging reagents for positive mode LC-MS chemical analysis.173-186
In LC-MS chemical analysis, the positive mode MS detection is often more sensitive than the negative mode, and is thus more frequently used. Since urine metabolomics requires use of methods with different selectivity, negative mode MS analysis can enlarge the range of detectable metabolites. In particular, anionic compounds generally respond well in negative mode MS. Anionic tagging reagents can be used to convert neutral or cationic compounds into anions. Anionic derivatization reagent DMF-SO3 has been used for analysis of alcohols in negative mode MS.(Figure 5) (187, 188) Research on anionic tags is much less extensive than the cationic tags. DMF-SO3 is susceptible to hydrolysis. SBA tagging usually has low derivatization yield and requires prolonged reaction at high temperature which could lead to degradation of analytes and side reactions. Thus, new anionic tagging methods are needed for facilitate metabolite analysis using negative mode MS.
Sulfur trioxide N,N-dimethyl formamide 2-Sulfobenzoic acid cyclic anhydride (SBA) (DMF-SO3) Figure 5. Two ionic tagging reagents for derivatization of metabolites for negative mode MS.
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1-5.3 Solid phase exaction of biological samples
Biological samples like urine have a complex matrix of chemicals at various concentrations. Direct
LC-MS analysis can produce complicated chromatograms and MS spectra. Also, the high abundance chemicals in the biological samples tend to interfere with detection of low abundance metabolites through ionic suppression and detector saturation. To this end, LC-MS experiments usually require pre- chromatographic separation of biological samples. One of the most used separation technique is solid phase extraction (SPE).(189) SPE works with the same mechanism as LC. The particle size of SPE adsorbent
(typically 30-60μm) is much larger than that of HPLC stationary phase (~3-5 μm), and thus the separation resolution of SPE is lower than HPLC. However, the resolution and selectivity of SPE can be higher than other separation methods such as precipitations and liquid-liquid extraction.(190) Compared to HPLC, SPE is cheaper and faster, and gives a higher sample loading capacity. Also, SPE can be used for high throughput separation via parallel conditions. These advantages make SPE is a good method for pre-chromatographic separation of urine metabolites for LC-MS analysis.
Just like HPLC, the stationary phase determines the selectivity of SPE. There are three common types of SPE: normal phase (polar), reverse phase (nonpolar), and ion exchange (ionic).(191, 192) The adsorbents of normal phase SPE have polar groups like diol, aminopropyl, cyanpropyl, unconjugated silica, alumina, magnesium silicate (Florisil®). These polar sorbent surfaces bind polar and ionic molecules by a variety of interactions such as dipole-dipole and dipole-ion interactions. Partitioning of molecules is also important. Solvents with low polarity can be helpful for binding of the analytes. The bound compounds are eluted with more polar solvents such as water or salt-water with or without an organic cosolvent. Since urine metabolites are in water, solvent exchange by liquid-liquid extraction or addition of a water-miscible solvent like acetonitrile, is often necessary before SPE to facilitate adequate binding. These additional steps and dilution of samples make normal phase SPE less useful for urine analysis.
Reverse phase SPE is commonly used for separation of aqueous sample like urine. Typical reverse phase SPE adsorbents include C18, C8, C6, C4, C2, phenyl, cyclohexyl and cyanopropyl. The latter can
Page 36 of 133 also by used as a polar adsorbent as just indicated. The hydrocarbon groups interact with analytes primarily by hydrophobic interactions. The groups with longer carbon chains bind the molecules stronger. The phenyl adsorbent has less hydrophobic interaction than common C18 phase, but the phenyl group can enhance retention of aromatic compounds through π-π stacking interactions. In water, the compounds with low polarity are retained by the reverse phase adsorbents. Less polar solvents such as ethyl acetate, tetrahydrofuran, isopropanol, methanol, and acetonitrile are used to elute the bound molecules. Because reverse phase SPE extracts less polar molecules from polar sample matrix, it is suited to separation of nonpolar urine metabolites for analysis by LC-MS.
Since many metabolites in the unmodified or the chemically derivatized urine samples have charges, ion exchange SPE finds important applications in the urine sample preparation process. Ion exchange SPE adsorbents are functionalized by ionic groups.(193) The negative functional groups are used for cation exchange SPE, while positively charged groups are used for anion exchange SPE. Ion exchange SPE can also be classified by whether the functional groups of adsorbents are strong or weak acid/base. Some common ion exchange adsorbents are listed in Table 5. Cationic compounds bind to cation exchange SPE, and anionic compounds bind to anion exchange SPE. Different types of ion exchange SPE can be used to separate analytes with strong acidic, weak acidic, strong basic, and weak basic groups.
Cation Exchange Adsorbent Anion Exchange Adsorbent
Strong Cation Exchange Weak Cation Exchange Strong Anion Weak Anion Exchange
(SCX) (WCX) Exchange (WAE)
(SAX)
Benzenesulfonic Carboxylic Quaternary Diethylaminoethyl
ammonium
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Propylsulfonic Propylcarboxylic
Table 5. Examples of ion exchange absorbents.
The bound ionic molecules can be eluted in three ways. First, solvent with high ionic strength (high salt concentration) can be used to weaken the electrostatic interactions between the analytes and adsorbent through the screening effect. Second, a solvent at pH different from the binding solvent can be used for elution. At a pH lower than the pKa of the acidic groups of analytes or the adsorbent, the anionic group will be protonated and become neutral. On contrary, the basic groups of analytes or the adsorbent will be deprotonated and become neutral at pH higher than their pKa. The third way to elute bounded ionic molecules is through competitive binding of high affinity ions in the elution solvent. The order of empirical binding affinity of some ions to the stationary phase ion exchangers with opposite charge are as follows.
Cations:
2+ 2+ + + 2+ 2+ 2+ + 2+ 2+ + + + + + Ba > Pb > Ag > Cu > Ca > Fe > Mg > K > Mn > Ba > RNH3 > NH4 > Na > H > Li
Anions:
− − − − − − − − benzene sulfonate > citrate > HSO4 > NO3 > HSO3 > NO2 > Br > Cl > HCO3 > HPO4 > formate > acetate > propionate > F− > OH−
Besides the traditional types of SPE, new SPE adsorbents have been developed.(194) For example, polymer-based SPE adsorbents can be used at a broader range of pH (from 0 to 14) than the silica-based
SPE which generally suffers hydrolysis of functional groups at low pH and hydrolysis of silica at high pH.
Polymer-based SPE could also have a high binding capacity due to their high surface area. In addition, separation using polymer-based SPE is less sensitive to flow rate than silica-based SPE. Another interesting
Page 38 of 133 type of SPE adsorbent is the molecularly imprinted polymers. The molecularly imprinted polymers are synthesized with a template molecule that has the same or similar structure as the class of analytes to be studied.(195, 196) Thus, the molecularly imprinted adsorbents have high selectivity and can greatly increase the sensitivity of the subsequent analysis of the selected molecules. (195, 196)
1-5.4 HPLC of complex biological samples for MS analysis
The metabolites in a complex biological sample can be grouped by their polarity and charge using
SPE. The pre-separated metabolites are still too complicated to be directly analyzed by MS spectrometry.
High performance liquid chromatography (HPLC) is the routinely coupled with MS spectrometer.(17) HPLC separates the metabolites into peaks eluted at different retention time. The selectivity of HPLC is the same as that of SPE described in the previous section. However, amongst the variety of stationary phases, only reverse phase HPLC has been widely used for LC-MS analysis. Solvent incompatibility limits the on-line application of normal phase and ion exchange HPLC in couple with MS. Nonpolar solvent is used in normal phase HPLC, but ESI ionization cannot be achieved in a nonpolar solvent.(197) Ion exchange HPLC usually uses high concentration salts to elute analytes. Salts in the HPLC fractions could cause ion suppression and form many adducts in MS spectrometers.(198)
The high separation resolution of HPLC can not only greatly simply MS spectra, but also add another characteristic variable, i.e. the retention time, of the metabolites to help with peak identification for known analytes. The resolving power of an HPLC column with given stationary and mobile phases increases as the stationary phase particle size decreases. (199, 200) The particle size of HPLC is typically between 3 to 5 μm. Although HPLC columns with smaller particles have higher resolution, they also require higher operating pressure. HPLC columns with 3 μm particles have typical operating pressure from 5 to 6 kpsi. Conventional HPLC system cannot provide pressure higher than 6 kpsi to use columns with particles smaller than 3 μm. To obtain better resolution, Ultra High Performance Liquid Chromatography (UHPLC) instruments have been developed. The maximum operating pressure of UHPLC systems can go up to 100
Page 39 of 133 kpsi.(201) Thus, UHPLC allows using sub 2 μm columns to achieve ultra high resolution.(202) Also, UHPLC experiments have much shorter run time than conventional HPLC.(203) Due to these advantages, UHPLC is an ideal choice for the LC-MS analysis of urine metabolome.
2. MATERIALS AND METHODS
2-1. Evaporative derivatization reaction with sulfobenzoic anhydride
We used 4-phenylphenol (4-PP) as a model phenol to optimize the reaction yield. As a control reaction method, we first employed the solution-based non-evaporative reaction to derivatize the phenolic compounds. This method was previously reported by Zu et.al.(204) In our experiment, we dissolved 0.05 mmol 4-PP, 0.5 mmol 2-sulfobenzoic anhydride (SBA), and 8 x10−4 mmol 4-dimethylaminopyridine
(DMAP) (DMAP: 4-PP w/w 2%) in 1 mL ACN. The reaction solution was incubated first at room temperature for 1 hour and then in an 80 °C sand bath (Reacti-therm, Pierce, Rockford, IL, USA) for 2 hours. The mixture solution after reaction was diluted 100 times with 20% ACN in water for the HPLC analysis.
In the evaporative derivatization reaction developed by us, we explored three different 4-PP concentrations: 5 × 10−2 M, 5 × 10−3 M, and 5 × 10−4 M. For each reaction, one equivalent of 4-PP, ten equivalents of SBA, and 2% DMAP (DMAP: 4-PP w/w) were dissolved in 1 mL ACN. We also studied a low 4-PP concentration sample which contains 5 × 10−6 M 4-PP, 5 × 10−3 M SBA and 1.6 × 10−7 M DMAP.
50-μL aliquot of the reaction solution was transferred into a HPLC vial with an insert, and evaporated in a
0.6-torr SpeedVac (Savant Instruments, Hyderbad, India) at room temperature for 40 minutes. After evaporation, the white solid of reaction mixture was incubated in a 60 °C sand bath for 1 hour. After the reaction, the solid was reconstituted with 50-μL 50% ACN in water. For the HPLC analysis, the reaction mixtures with 5 ×10−2 M, 5 ×10−3 M, and 5 ×10−4 M 4-PP were diluted respectively by 100-fold, 10-fold, and 10-fold with 20% ACN in water. For MALDI-MS analysis, a 5-µL aliquot of the reconstituted reaction
Page 40 of 133 mixture solutions was mixed with 10-µL CCA matrix solution in ACN. 1-µL of the MALDI sample was spotted on the MALDI sample plate for the MS analysis.
For the phenol mixture study, we dissolved 15 phenolic compounds (listed in Table 11 Section 3-
1-2), SBA and DMAP in 1-mL ACN to achieve final concentrations 5 × 10−4 M of each phenol, 5 × 10−3
M of SBA, and 2% (w/w of total phenols). The reaction mixture was subjected to the evaporative reaction and then analyzed by HPLC and MALDI MS following the same procedures described above.
2-2. Preparation of PEP bags for exaction of urine metabolites
To conduct the metabolic analysis of urine samples, it is important to enrich low abundance chemicals in urine samples and reduce degradation of the chemicals during storage and transport of the samples. We have developed motorized porous extraction paddles (PEP) for sample collection of urine chemical analysis.
We found that PEP with two types of adsorbents are useful for urine chemical analysis. The
Carboxen PEP contains the adsorbent 350–860 μm Carboxen-1003 (I124475) from Supelco (Bellefante,
PA, USA). The other type of PEP is the mixed particulate adsorbent PEP (MP-PEP). The MP-PEP contained equal amounts of six adsorbents, all from Supelco (Bellefante, PA, USA), including: 50 μm
Silica-octadecyl” (DSC-18/SP19381), 50 μm Silica-phenyl (DIS-Ph/SP13625), 55–60 μm Hydrophilic-
Modified Styrene Polymer (HLB SPE/media), 50 μm Silica-ethylphenyl sulfonate (DSC-SCX/SP18321),
50–160 μm Polyamide Resin (DSC-DPA-6S/SP 10627), and 50 μm Silicapropyltrimethylamine (DSC-
SAX/SP18957). The adsorbent particles were mixed by dry-tumbling a mixture of equal amounts by weight of the six adsorbents for 5 min using a rotary evaporator at atmospheric pressure.
Another adsorbent we used to prepare PEP is Carboxen-1003 from Supelco. Carboxen-1003 is a carbon molecular sieve that has multi-scale pores. The porosity, i.e., the volume of void space, of
Carboxen-1003 is 0.38 cm3/g at the microscopic level, 0.26 cm3/g at the mesoscopic level, and 0.28 cm3/g
Page 41 of 133 at the macroscopic level. The micropores of this adsorbent are 5-8 Å. The surface area of the adsorbent is
1000 m2/g. In addition, a PEP was made with the Empore SDB-XC disk, a polystyrenedivinylbenzene membrane from 3 M Purification Inc. (St. Paul, MN, USA).
2-gram of the adsorbent particles were placed into a N25 mesh (25-μm pore) nylon bag (Industrial
Products Corp., Minneapolis, MN, USA). The bag was sealed using a heat sealer 530-166S S/S
CRYOBAND (Accu-Seal, San Marcos, CA, USA). The nylon bag has a dimension 6.5×7.0 cm outside and
6.0×6.5 cm inside. The sealed nylon bag was immobilized between two stainless steel sheets, Tefzel
Tiewraps (T-TEFZEL-04, Tiewraps.com, San Diego, CA, USA). The Tiewraps were tied together and attached to the motorized PTFE shaft. After the PEP was assembled, it was washed sequentially with five solvents: acetone for 6 hours; isooctane/methanol/acetone 0.25/0.25/0.50 v/v/v overnight; methanol/water/ammonia 0.20/0.80/0.012 v/v/v for 3 hours; methanol/water/acetic acid 0.20/0.80/0.012 v/v/v for 3 hours; methanol/water 0.20/0.80 for 3 hours.
Malachite Green (a carcinogen) was used to test chemical adsorption of PEP. 10-mg Malachite
Green was dissolved in volumetric flask to prepare 100-mL stock solution in water with 4% acetic acid.
10-mL stock solution was added to 1.8-L water with 4% acetic acid for PEP extraction. The PEP was stirred by a motor at 190 rpm. Aliquots of the solution were taken over time to measure the visible absorbance at
619 nm. For the extraction with min-PEP, 10-μL Malachite Green stock solution was added to 1.8-mL water with 4% acetic acid in a 2-mL vial. The mini-PEP was made of 10-mg MP adsorbent in a nylon bag
0.6 × 3cm outside and 0.3 × 2.5cm inside. The vial with mini-PEP was shaken at 230 oscillations per minute.
Page 42 of 133
2-3. Urine sample collections
Seven urine samples were used in this study with IRB approvals. Seven Puerto
Rico pregnant women have been recruited by the School of Medicine at University of
Puerto Rico. The urine samples were collected by the individuals at home following the urine collection guidelines made for this study. (Figure 6) The first morning urines were accumulated over one week to 1.8-liter total volume in the collection jar kept in dark. 200 mL 40% Figure 6. The urine collection guidelines for participants of this acetic acid was added in the jar before sample study to collect urine samples at home. collection for preservation of urine. Then, the urine samples were transferred to the hospital at University of Puerto Rico and extracted by the local nurses using the MP PEP extraction paddle (containing 2.0 g mixed particulate adsorbents) provided by our lab. The urine sample on PEP bags were stored at ‒20°C and shipped on dry ice to our lab in Boston by overnight mail. Upon receiving the samples, we immediately processed the PEP bags for storage. The PEP bags were first stirred and washed in 2-L water. The nylon bags were removed from the Tiewrap, gently blotted with Kimwipe, and put in a desiccator with Drierite.
When the bag is dry, it is cut open to retrieve the MP PEP adsorbent beads. The PEP beads were transferred into a 5-mL Cryoware vial. The vial was gently inverted 20 times and stored at ‒80°C for future chemical analysis.
Page 43 of 133
2-4. Direct MALDI-MS analysis of urine metabolites extracted by MP-PEP
A 1.8-L urine sample from Puerto Rico was extracted using the regular PEP with 2.0g MP adsorbents at room temperature for 30 hours. The PEP was washed by stirring in water for 1 hour. 5-mg of dried MP-particles was taken from the washed PEP for further analysis, and eluted in 200-μL 40% acetonitrile solution in water with 20-mM triethylammonium acetate TEAA (Sigma Aldrich, St. Louis, MO,
USA) for 20 minutes. The sample was then centrifuged at 4000g for 10 seconds. 2-μL supernatant was mixed with 20-μL 5mg/mL α-cyano-4-hydroxycinnamic acid (CCA) (Sigma Aldrich, St. Louis, MO, USA) matrix in 50% ACN in water. 0.7-μL of this solution was pipetted to each spot on the MALDI sample plate.
MS analysis was conducted by a MALDI TOF/TOF mass spectrometer (5800, AB SCIEX, Foster City, CA,
USA) in both positive and negative ionization mode. Each spectrum was an average of 400 laser pulses with a 150-ns delay time. For MS/MS analysis, Collision Induced Dissociation (CID) of the selected precursor ions within a mass resolution window of 400 was achieved in CID chamber filled with air. The metastable ion suppressor was on.
For the quantitative analysis of PEP extraction yield, the urine sample was spiked with three standard compounds, i.e., thiamine d3 HCl (Toronto Research Chemicals, Toronto, Canada, M3J2J8), L-
Carnitine: HCl, O-octanyl [N-methyl-d3] (Cambridge Isotope Laboratories, Tewksbury, MA, USA) and, and reserpine (Sigma Aldrich, St. Louis, MO, USA). Two identical 1.8-L urine samples were used in this experiment. One was not spiked and directly subjected to MP-PEP extraction followed by MALDI MS analysis as a blank control. The other urine was spiked with 400 nmol of each standard, and then extracted using MP-PEP. After extraction, PEP was washed with water and air dried. 5-mg aliquots of the MP adsorbents were taken for analysis. The metabolites on the MP adsorbent particles were first eluted with
100-μL 20mM TEAA in 30% ACN aqueous solution by shaken at 250 rpm for 20 minutes. After centrifuged, the supernatant was recovered. The adsorbent particles were extracted again with 100-μL
20mM TEAA in 70% ACN aqueous solution. The supernatants from two elution were combined. To prepare MALDI MS sample, 1-μL combined supernatant was mixed with 9- μL CCA matrix. 0.7-μL sample
Page 44 of 133 was deposited on MALDI plate for each spot. In addition, a 10-μL spiked MS sample was spiked again with 2-pmol each standard compound for calibration of MS peak intensity. The MALDI MS spectra in positive ionization mode were obtained by averaging 1200 laser pulses with a 120-ns delay time.
2-5. Optimized sample preparation method for UHPLC-MALDI MS analysis
As described in section 2-2, from each subject in this study, 1.8-L urine sample was collected on
2.0 grams of PEP adsorbents. For each LC-MS metabolic analysis experiment, a 30-mg aliquot of the adsorbents was placed in a 1.5-mL Eppendorf centrifugal tube. The urine components on the adsorbents were first eluted with 0.5-mL 30% ACN 10% triethylammonium acetate in water by shaking at 1750 rpm in a pulsing vortex mixer for 30 minutes. Then, the particles were spun down at the speed level 7 for 1 minute in microcentrifuge (Marathon Micro H, Fisher Scientific, Waltham, MA, USA). About 450-μL supernatant was carefully pipetted into another Eppendorf tube, and centrifuge again for 1 minute to further remove particles. About 400-μL supernatant was obtained from this elution process. The adsorbent particles after elution were extracted again by 0.5-mL 80% ACN 10% triethylammonium acetate in water. The second round of elution also generated 400-μL supernatant. The two eluted supernatants were combined and brought to 4-mL total volume with DI water.
In our study, we found preliminary separation of the extracted urine sample using solid phase extraction
(SPE) greatly increased the sensitivity of UHPLC-MALDI
MS detection of urine metabolites. Since our study focused on discovery of sulfate conjugated metabolites, we chose to use a weak anion exchange SPE cartridge (Strata X-AW Figure 7. The weak anion exchange SPE cartridge used in our study. 33 μm, 200mg/3mL, Phenomenex, USA) for the preliminary separation and enrichment of analytes. The SPE cartridge (Figure 7) was prewashed with 2-
Page 45 of 133 mL methanol by gravity, and then by 2-mL DI water. 4-mL of the urine sample eluted from PEP particles was loaded on the cartridge. Then, the cartridge was washed by 4-mL 25-mM ammonium acetate by gravity followed by 4-mL methanol. Finally, the analytes on the cartridge was eluted by 2-mL 5% ammonium hydroxide in 50% methanol. The eluates were dried in a SpeedVac at room temperature for two and half hours. The solid was redissolved in 250-μL 1% ACN 10% triethylammonium acetate in water. After removing the residual undissolved solids by centrifugation, ~200-μL supernatant was pipetted into a HPLC vial for subsequent LC MS analysis.
2-6. HPLC and UHPLC
In our experiments of anionic derivatization of phenolic compound, the yield of reactions was measured by regular HPLC UV analysis. The derivatized urine samples were prepared for HPLC analysis as described in section 2-3. 10-µL of the sample was injected into a C18 HPLC column (AQUASIL, 150 ×
2.1 mm, 5 µm, Fisher Scientific, USA). HPLC experiments were run at room temperature using a Hewlett
Packard Series 1100 HPLC system. The mobile phase condition was 3 minutes 2% ACN in water followed by a gradient to 50% ACN over 13 minutes and 100% ACN for 5 minutes. The flow rate was 0.21 mL/min.
The UV detector was set to 256 nm.
To analyze urine extracts, we used the Dionex UltiMateTM 3000 RSLC nano system (Thermo
Scientific, Sunnyvale, CA, USA) and the capillary Acclaim PepMap RSLC C18 column (300 μm×15cm,
2μm, Thermo Scientific, Sunnyvale, CA, USA) with the C18 trap column PepMap 100 μ-precolumn (300
μm×5cm, 5μm, Thermo Scientific, Sunnyvale, CA, USA). The columns were equilibrated at 30 °C. For each experiment, 5-μL urine extract was injected to the trap column and washed by 1% ACN with 20 mM triethylammonium acetate to the waste for 4 minutes at 20μL/min. Then, the trap column was connected to the analytical column and eluted by a gradient from 10% ACN to 80% ACN over 100 minutes followed by
80% ACN for 4 minutes. UV absorbance were measured at 220 nm, 260 nm, and 320 nm. The UHPLC
Page 46 of 133 elute fractions were also collected 20 seconds per droplet on a MALDI plate (Opti-TOF 384 well insert,
123 ×81 mm, ABSCIEX, Framingham, MA, USA). A matrix solution (0.5-μL 5mg/mL CCA in 50% ACN with 7 mM ammonium phosphate dibasic) was added to each spot on the MALDI plate by manual pipetting.
2-7. MALDI TOF MS and TOF/TOF tandem MS
The MALDI samples prepared manually or from UHPLC were subjected to MALDI MS analysis using a MALDI TOF/TOFTM 5800 system (AB SCIEX, Framingham, MA, USA). The MS specter was set to either negative or positive ionization mode as needed in each experiment. TOF analyzer worked in reflectron mode with a 100-ns delay time. Each MS spectrum arose from the average of 1200 laser pulses.
The laser intensity was set to ~2500 for MS analysis.
Two ways were used to generate ion fragments for MS/MS analysis. In the phenolic compound derivatization experiment, a higher laser intensity ~3500 was used to achieve laser-induced-dissociation
(LID) with the metastable-suppressor turned on and the CID turned off. In the urine metabolic analysis,
1kV negative voltage and ~1 × 10‒6 mmHg collision gas in CID chamber were used to produce fragments.
The precursor ions were automatically selected by the software PeakExplorer (AB Sciex).
2-8. Enzymatic deconjugation and cationic tagging of urine
Using the method described in the section 2-3, we prepared 800-μL urine extract from 30-mg urine sample PEP beads. For each deconjugation experiment, a 20-μL aliquot of the urine extract was dried in a speed-vac. Based on the estimation described in the section 3-3, the dried urine extract contains approximately 0.5-μmol sulfate conjugates. Each dried urine extract sample was then reconstituted with
19-μL aqueous buffers. The buffer conditions examined in our study include 10-mM MES buffer at pH 5.0,
Page 47 of 133
10-mM MES buffer at pH 6.0, and DI water at pH 7.0. Then, 1-μL of enzyme stock solution was added into the urine sample to catalyze the deconjugation reaction. The reaction occurred during incubation at
37°C for 1 hour or 2 hours.
For cationic tagging reaction, 10-μL deconjugated urine sample was mixed with 2-μL of 12 mg/mL
CAX-B tag and 120 μg/mL triethylamine. The reaction mixture sat at 38 °C overnight, and then was dried in SpeedVac. The solid was reconstituted in 50- μL 5% ACN in water. 2.5- μL solution was used for the
UHPLC MALDI MS analysis.
3. RESULTS AND DISCUSSION
3-1. Evaporative derivatization of phenols with sulfobenzoic anhydride for negative-mode MALDI-MS
One challenge in metabolomic study using MALDI-MS is that the uncertainty of ionization efficiency for the metabolites. In general, the metabolites without ionic groups may have low ionization efficiency using the soft ionization MS methods like MALDI and ESI. Inefficient ionization results in low sensitivity. Therefore, direct analysis of unmodified urine samples with MALDI MS could miss many low concentration metabolites, especially those without ionic groups. To exploit the use of MALDI-MS method for metabolites detection, various chemical derivatization methods could be applied to introduce specific ionic groups. Metabolite derivatization not only increases ionization efficiency of some classes of metabolites, but also make the subsequent MS/MS analysis more selective by detecting the fragment or mass loss of the characteristic group introduced by ionic tagging. The metabolite derivatization methods can be classified into cationic tagging and anionic tagging. The cationic tagged molecules could be positively charged after ionization and thus suits for positive-mode MS analysis which detects cationic analytes. Likewise, the anionic tagged samples are usually more suitable for negative-mode MS experiments to analyze negatively charged metabolites. Therefore, use of different ionic tagging techniques
Page 48 of 133 in addition to direct MS analysis can greatly expand the scope of urine metabolome discovery by MALDI
MS.
3-1.1. SBA evaporative derivatization reaction and MALDI MS analysis of a model phenol (4-phenyl- phenol)
Here, we first developed an evaporative anionic tagging method using 2-sulfobensoic acid cyclic anhydride (SBA,
Figure 8) for negative mode MALDI MS analysis of metabolites. (Figure 9) SBA have been successfully used in previous studies for tagging peptides and a variety of alcohols, Figure 8. An anionic tagging agent SBA: 2- sulfobensoic acid cyclic anhydride. including sugars and phenols, to increase sensitivity of MALDI analysis. However, the relative low yield and long reaction time of the reported SBA derivatization methods limit the usefulness of its application in MALDI MS analysis. In this light, we developed a new SBA reaction method to derivatize phenols. Phenolic compounds ubiquitously exist as endogenous and dietary metabolites as well as environmental and pharmaceutical xenobiotics.
Figure 9. Derivatization of phenolic metabolites by SBA for subsequent MALDI-TOF-MS and MS/MS in negative ion mode.
Page 49 of 133
To development the derivatization method, we have used 4-phenylphenol as a model phenolic molecule. Phenylphenol (C12H10O) is a small organic molecule with molecular weight of 170.211 g/mol. It is commonly used as disinfectant, food additive, and topical antiseptic agent. Therefore, it is a common contaminant in our environment and could exist in human body as xenobiotics. we found that the non- derivatized 4-phenylphenol cannot be directly detected by MALDI MS (Figure 10). The MS spectrum of the 4-phenylphenol sample shown in Figure 10A does not show the peak at m/z = 169 which corresponds
- to the molecular ion peak (C12H9O ). This result is attributed to the poor ionization of phenylphenol in
MALDI ionization process. Therefore, 4-phenylphenol needs to be modified for the MALDI MS analysis.
TOF/TOF™ Reflector Spec #1=>MC[BP = 779.1, 97988] 171.023 100 4288 90 (A) 80
70 170.015
60 166.002 172.029
50 166.188
% Intensity 40
30
20
10
0 164.60118 166.31016 168.01914 169.72812 171.43710 173.14608 Mass (m/z) <
60 166.203 170.024 172.039 50
% Intensity 40
30
20
10
0 164.60118 166.31016 168.01914 169.72812 171.43710 173.14608 Mass (m/z)
Figure 10. The MALDI (negative mode) MS spectra of the analyte sample of (A) unmodified 4-phenylphenol (~1nmol/spot), and the control sample (B) the MALDI matrix, alpha-cyano-4-hydroxycinnamic acid (CCA). The spectrum of unmodified 4-phenylphenol sample is indistinguishable from that of control sample.
Then, we chemically tagged 4-phenylphenol with SBA using the previously reported solution phase derivatization method. The chemical reaction of this derivation is shown in Figure 11.
Page 50 of 133
SBA,
in acetonitrile, heat
Figure 11. Derivation of 4-phenylphenol with SBA. This derivatization of 4-phenylphenol introduces a permanent negative charge to the molecule and thus enables higher tendency of ionization and thus easier detection by MALDI MS. The derivatized 4- phenylphenol in the reaction mixture was purified by reverse phase HPLC. The elute fraction was collected and analyzed by MALDI MS. In Figure 12A, the MS spectrum of the sample, containing ~0.2 nanomole of
- the derivatized 4-phenylphenol (C19H13O5S ) per spot, has a strong intensity peak at 353.046 which
- corresponds to the exact mass of C19H13O5S . We observed that the matrix shows a much lower intensity peak at 353.021 (Figure 12B). Despite this closely located peak of CCA matrix, the derivatized 4- phenylphenol can be easily distinguished from the matrix after spectra calibration.
TOF/TOF™ Reflector Spec #1=>MC[BP = 779.1, 99276]
100 9.9E+4 90 (A) 353.046 80
70
60
50
% Intensity 40
30
20
10
0 352.75636 352.91765 353.07893 353.24022 353.40150 353.56279 Mass (m/z) <
100 9.9E+4 90 (B) 80
70
60
50
% Intensity 40
30
20 353.021
10
0 352.75636 352.91765 353.07893 353.24022 353.40150 353.56279 Mass (m/z)
- Figure 12. MALDI (negative mode) MS spectra of (A) modified 4-phenylphenol (C19H13O5S ) (~0.2 nmol/spot) and (B) CCA matrix.
Page 51 of 133
To further confirm the identity of the analyte, we have conducted fragmentation analysis by negative ion MALDI-TOF/TOF-MS of the derivatized analyte. In Figure 13A, the MS/MS spectrum shows that the parent ion with a mass to charge ratio of 353.05 produces a fragment peak at 169 corresponding to
- the fragment of C19H13O5S after a loss of the tag. The MS/MS spectrum of CCA matrix does not show peak at 169. Therefore, we conclude that the derivatization of 4-phenylphenol is successful and the derivatized
4-phenylphenol can be detected and identified by MALDI MS.
TOF/TOF™ MS/MS Precursor 353.05 Spec #1[BP = 168.9, 39517] 169 100 4.0EE+4 90 (A) 169 80 O 70 60 O 50 -O3S
% Intensity % 40 30 144 20 343353 10 208 354 81 142 235 311 341 0 9 82 155 228 301 374 Mass (m/z) <
100 4.0EE+4 90 (B)
80 70 60
50
% Intensity % 40 30
20
10 144 353 208 235 311 343350 0 9 82 155 228 301 374 Mass (m/z) Figure 13. MALDI MS/MS spectra of the parent ion at m/z=353.05 for (A) modified 4-phenylphenol (C19H13O5S‒) (~0.2nmol/spot) and (B) pure CCA matrix.
Page 52 of 133
In urine samples, 4-phenylphenol most possibly exists at trace levels. The yield of the derivatization reactions is crucial for the further detection by MALDI MS. The high yield with high reproducibility is most favorable for the further analysis. Thus, we have explored various reaction conditions and have established a novel reaction scheme for the derivatization of 4-phenylphenol. In the first stage of exploring the optimized scheme for derivatization reaction, we have conducted a series of reactions in anhydrous acetonitrile at different temperatures and concentrations of reactants. The yield was calculated based on the integrated areas of the labeled 4-phenylphenol peak and the unlabeled 4-phenylphenol peak in HPLC chromatogram. (Figure 14A) The yields of different reaction conditions are listed in Table 6.
In Table 6, we found that the reaction in 80°C sand bath has relatively high yield ~46%. However, even in the sealed vials, the tendency of evaporation of the reaction solution at high temperature is high. And the variant extents of evaporation lead to very different yields, and thus the reproducibility is hard to achieve. The reaction in solutions at room temperatures have very low yield even with a prolonged reaction time. At room temperature, the length of the reaction time has little effect on the yield. Importantly, we noticed Figure 14. Reverse phase HPLC chromatograms of the reaction mixture of 4-phenylphenol (4PP) SBA- that higher reactant concentrations in the solution tagging reaction. (A) solution-based reaction at 80 °C for 2 hours. (B) Evaporative reaction at 60 °C leads to higher yield. This result suggests that the for 1 hour. Subsequent MALDI MS analysis showed peak 1 is SBA-4PP and peak 2 is underivatized 4PP. yield could be increased by concentrating the sample.
Page 53 of 133
Reaction Conditions
Concentration Yield Temperature Time (hour) 4phenylphenol: SBA
0.05M:0.5M 80 °C 2 63.2±22.2% (n=5)
0.05M:0.5M Room Temperature 24 3.3% (n=1)
0.005M: 0.05M Room Temperature 48 2.6±0.07% (n=2)
0.0005M: 0.005M Room Temperature 48 0.97±0.03% (n=2)
Table 6. Yield of solution phase derivatization reactions of 4-phenylphenol at different reaction conditions.
Therefore, we have used SpeedVac (vacuum concentrator) to concentrate the reactant solutions at room temperature. After 40 minutes in SpeedVac, the reactant mixtures were completely dried by visual inspection and formed a white solid. Interestingly, we found that the reaction took place in the solid phase reactant mixtures. (Figure 15) The reactant mixtures were kept at room temperature after drying by
Figure 15. Evaporative SBA tagging reaction for 4-phenylphenol. The picture shows the reaction mixture after evaporation in a SpeedVac.
SpeedVac. We redissolved the solid samples after several different periods of time, and then measured the yield by HPLC. The results are summarized in Table 7, where it is shown that the yield of the derivatized
‒ 4-phenylphenol (C19H13O5S ) in the solid phase increases with time. After 3 days at room temperature, the yield is comparable to that obtained in solution phase reaction at 80°C.
Page 54 of 133
Time (hour) Yield
0 1.8% (n=1)
1 3.0% (n=1)
5 9.9% (n=1)
24 33±4% (n=3)
48 37±7% (n=2)
72 48±2% (n=2)
Table 7. Yield of derivatization reaction in solid phase at room temperature at different time lengths. The reactants are from concentrating of 50-uL of 0.05M 4-phenylphenol, 0.5M SBA, and DMAP (2% w/w of 4-phenylphenol).
To further increase the yield of derivatization reaction, we have studied the effects of temperature on the solid phase reactions. In Table 8, the results show that 60°C is the optimum temperature to obtain the high yield. Further, we have shown that the reaction time can be reduced to 1 hour without compromising the high yield (Figure 14B, Table 9).
Temperature (°C) Yield
40 53±11% (n=3)
60 97.2±0.2% (n=3)
80 98.0±0.3% (n=3)
Table 8. Yield of solid phase derivatization reaction at different temperature for 2 hours. The reactants are from concentrating of 50-μL of 0.05M 4-phenylphenol, 0.5M SBA, and DMAP (2% w/w of 4-phenylphenol).
Time (hour) Yield
1 95.5±0.8% (n=8)
2 97.2±0.2% (n=3)
Table 9. Yield of solid phase derivatization reaction at 60°C for different time lengths. The reactants are from concentrating of 50-μL of 0.05M 4-phenylphenol, 0.5M SBA, and DMAP (2% w/w of 4-phenylphenol).
Page 55 of 133
In the solid phase reaction, one would expect the concentration of the reactants in the initial solution would not affect the yield of the solid phase reaction. It is indeed true at initial concentration of 4- phenylphenol above 10‒4 M (Table 10). At initial concentration of 10-5 M, the yield started to decrease but still sufficiently high for MALDI MS analysis.
Concentration of Concentration of SBA Yield 4-phenylphenol (M) (M)
5×10-2 5×10-1 95.5±0.8% (n=8)
5×10-3 5×10-2 94±1% (n=3)
5×10-4 5×10-3 94.3±0.6% (n=3)
5×10-5 5×10-4 50±10% (n=4)
Table 10. Yield of the 4-phenylphenol : SBA, DMAP (2% w/w of 4-phenylphenol) solid phase derivatization reaction at 60 °C for 1 hour at different initial concentrations of the reactants in solution.
Even at 10-6 M initial concentration of 4-phenylphenol (corresponding to the further sub-picomole analyte in MALDI analysis), the derivatized product of the solid phase reaction at 60 °C for 1 hour is still
‒ sufficient for MALDI MS analysis. In Figure 16, it is shown that the peak of C19H13O5S at 353.050 (Figure
16A) clearly is distinct from the CCA matrix (Figure 16B). Further fragmentation analysis by MS/MS
‒ confirms the labeled product by the detection of fragment C12H9O (4PP‒H) at m/z=169 (Figure 17A) which is not shown in CCA matrix (Figure 17B).
Page 56 of 133
TOF/TOF™ Reflector Spec #1=>MC[BP = 779.0, 95596]
100 (A) 7.5E+4 90 359.077 80 O 70
60 O 50 -O3S 360.081
% Intensity % 40 30 20 353.050 361.087 351.033 355.083 10 343.034 340.044 345.079347.079349.087351.107 355.291357.105 359.701 362.089 370.119 0 340.0 346.8 353.6 360.4 367.2 374.0 Mass (m/z) <
80 359.068
70 60 50
% Intensity % 40 360.073 30 355.073 20 361.079 351.026 354.084 10 343.025 356.083 340.048 345.091347.073 350.054 358.075359.692 362.080 370.112 0 340.0 346.8 353.6 360.4 367.2 374.0 Mass (m/z)
-6 Figure 16. MALDI (negative mode) MS spectra of (A) product of solid phase reaction with 5μL of 5x10 M 4-phenylphenol in initial solution, and (B) CCA matrix.
Page 57 of 133
TOF/TOF™ MS/MS Precursor 353 Spec #1[BP = 310.8, 2303] 311 100 2303 90 (A) 343
80
70
60 O
50 144 % Intensity 40 O 30 344
-O3S 20 169 210 310 10 341349 142 157188197 208217226235 290 308 327 0 9 82 155 228 301 374 Mass (m/z) <
80
70
60
50
% Intensity 40 144 344 30
20 210 10 309 341 25 142 188197 208 225233 316 328 349 0 9 82 155 228 301 374 Mass (m/z) Figure 17. MALDI MS/MS spectra of the parent peak at m/z=353.05 for (A) the product of solid phase reaction with 10-6M phenylphenol in initial solution, and (B) CCA matrix.
Page 58 of 133
In summary, our experiments on 4-phenylphenol demonstrated that the new evaporative derivatization reaction produces high yield of SBA-tagged phenolic compounds in short time and relatively low temperature. The improved tagging method can markedly increase the sensitivity of MALDI MS for detection of low concentration of phenolic metabolites in urine samples.
3-1.2. Anionic Tagging and MALDI MS analysis of a 15-phenol mixture
It is natural to hypothesize that the evaporative SBA tagging reaction can be used in MALDI MS analysis of other phenolic compounds. The general scheme of the tagging reaction followed by MS and
MS/MS analysis is illustrated by Figure 18. The SBA-tagging could increase the sensitivity of phenol detection in MALDI MS and produce the characteristic R-phenolate fragments in MS/MS analysis which confirm the identity of the phenol peaks in MS spectra.
Figure 18. A scheme of general SBA-tagging reaction of phenolic compounds for MALDI MS and MS/MS analysis. R represents the apo-phenol moiety of phenolic compound.
However, from the perspective of chemical reactivity, the very same SBA-tagging reaction can have different yields for different phenols. Therefore, we then evaluated the efficiency of SBA-tagging reaction and MALDI MS detection for a mixture of 15 phenolic compounds. The phenolic compounds used in this study are listed in Table 11. A 50 μL mixture solution in acetonitrile containing 5x10-4 M each phenol,
5x10-3 M SBA, and 1.6x10-5 M DMAP was used to perform the evaporative derivatization reaction at 60 °C
Page 59 of 133 for 1 hour. The SBA-tagged phenol mixture was then subjected to negative ion mode MALDI MS and
MS/MS analysis. The MS spectrum in Figure 19 shows that ten SBA-tagged phenolic compounds (#1-10) have been detected, even though three of them (#8,9, 10) having low signal intensity. The other five phenols
(#11-15) were not detected. We assigned the highest MS signal intensity (4-nonylphenol) as 100. The relative signal intensity and m/z of the phenols in the MS spectrum (Figure 19) and the phenolate fragments
(after loss of the SBA tag) in the MS/MS spectra are summarized in Table 11. Table 11 also reports the pKa (minus logarithm of the association constant) of the hydroxyl group of the phenols.
Figure 19. Negative mode MALDI MS spectra of (A) a mixture of 15 phenolic compounds in Table 11 derivatized by evaporative SBA tagging reaction and (B) the reaction blank without phenol mixture.
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Deprotonated R-Phenolate Number Structure molecule by by TOF/TOF pKa TOF (m/z) (m/z) 1 100 100 10.4 (403.158) (219.17)
2 29.5 16.5 9.6 (353.048) (169.07)
3 25.0 4.0 10.6 (305.048) (121.07)
4 12.3 3.8 9.6 (324.994) (141.01)
5 11.6 7.1 9.6, 11.3 (411.090) (227.11)
6 8.6 1.1 10.3 (291.033) (107.05)
7 6.4 1.0 10.0 (277.017) (93.03)
Cl 8 0.3 0.1 7.9 HO Cl (344.939) (160.96)
OH 0.1 0.2 9 and 10 7.2 (322.002) (138.02) O 2N
O 2N 11 N/D N/D HO NO 2 4.3 (381.003) (197.02)
O 2N 12 N/D N/D 4.1 HO NO 2 (366.987) (183.00)
Cl 13 N/D N/D 8.6 HO (310.978) (127.00)
Cl 14 N/D N/D HO Cl 6.1 (378.900) (194.92) Cl Cl Cl 15 N/D N/D HO Cl 4.7 (446.822) (262.84) Cl Cl
Table 11. The 15 phenolic compounds in the mixture: 1) 4-nonylphenol; 2) 4-phenylphenol (4PP); 3) 2,4- dimethylphenol; 4) 4-chloro-3-methylphenol; 5) bisphenol A (BPA); 6) o-cresol; 7) phenol; 8) 2,4-dichlorophenol; 9) 2-nitrophenol; 10) 4-nitrophenol; 11) 2-methyl-4,6-dinitrophenol; 12) 2,4-dinitrophenol; 13) 2-chlorophenol; 14) 2,4,6-trichlorophenol; 15) pentachlorophenol. ND stands for “not readily detected”.
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The results of MS analysis of SBA-tagged phenol mixture in Table 11 clearly show that the
effectiveness of this method varies over a broad range for different phenolic compounds. The low MS
response of the phenolic compounds (#8-15) could be due to many factors, e.g., inefficient derivatization,
unstable SBA-tagged molecules, or low desorption efficiency during MALDI ionization. Interestingly, the
high MS response compounds in Table 11 (#1-7) all have the phenol hydroxyl group with pKa higher than
that of the low MS response phenols (#8-15). It is a plausible speculation that the derivatization reaction
may have lower yield for the more acidic phenols (low pKa). To examine this speculation, we measured
the yield of SBA-tagging for pentachlorophenol (#15) at various temperature using reverse phase HPLC
with UV detection. (Figure 20, Table 12) Table 12 shows that derivatization of this low pKa phenol, even
at high temperature and prolonged reaction time, indeed has substantially lower yield than that of the model
phenol, 4-phenylphenol shown previously.
Reaction Conditions Yield
Temperature Time (hour)
60 °C 2 1%
80 °C 2 2%
100 °C 2 25%
Figure 20. HPLC chromatography of the SBA tagging reaction Table 12. The yield of the SBA-tagging of mixture for pentachlorophenol at 100 °C for 2 hours. Peak 1 and pentachlorophenol at various temperature for 2 2 are the SBA-tagged pentachlorophenol and the underivatized hours. pentachlorophenol, respectively.
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To gain further insight, we conducted MALDI MS and MS/MS analysis on the peak 1 in Figure 20.
− It is intriguing to find that, in the MS spectrum, three detagged phentachlorophenol signals ([C6Cl5O] m/z
264.839, [C6Cl5O + CCA − H + Na]− m/z 475.853, and [C6Cl5O + C6Cl5O +Na]− m/z 552.651), instead of the SBA-tagged pentachlorophenol, were detected. Therefore, the low response of the acidic phenols in
Figure 18 can be attributed to the combining effect of low derivatization yield and loss of SBA tag and spreading of signals during ionization.
We then examined if these more acidic phenolic compounds can be detected in other settings of
MALDI MS experiment. Indeed, we found two alternative MALDI methods worked for these phenols. First, when the peak 1 in Figure 20 was analyzed in the positive-ion mode of MALDI, a sodium adduct of the
SBA-tagged pentachlorophenol [M−H+2Na]+ m/z 492.810 can be readily detected. Previously, we noticed that the tag-free pentachlorophenol was detected in the negative-ion mode MALDI MS analysis. This observation prompted us to analyze the underivatized 15-phenol mixture in the negative-mode MALDI MS.
Interestingly, we found the underivatized acidic phenolic compounds (#8-15) can be detected by MALDI and the compounds (# 9, 10, 11, 12 and 15) have given strong MS signals. On contrary, the compounds
(#1-7) that were readily detectable after derivatization, were not detected or produced weak signals without
SBA tagging.
We concluded that the evaporative SBA-tagging followed by both negative and positive ion
MALDI analysis provide a complementary method for detecting various phenolic compounds. As discussed before, one central philosophy of nontargeted metabolomics study is to maximize the metabolite discovery through applying multiple analytical platform with different selectivity. That being said, the combination of direct MALDI analysis and chemical derivatization can find valuable applications in the study of urine metabolome.
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3-2. Development of Porous Extraction Paddle (PEP) for urine metabolite extraction
In most metabolic studies, the practical goal is to establish a correlation between a known or unknown urine metabolite and a medical condition in question. For example, the analytical methods developed in this dissertation study are intended to be used in a bigger project, NIH PROTECT program project, for analyzing large number of urine samples from pregnant women in Puerto Rico. The goal of
PROTECT is to examine the relationship between pollutant exposure and high preterm birth rate in Puerto
Rico. In such correlation analyses, it is important to reduce the sampling variation for individuals.
Therefore, urine samples for these metabolomic analyses are often collected at different time and combined to produce average individual metabolite profiles. The combined volume of individual urine sample can be quite large, e.g., our urine samples were extracted from 1.8-L urine from each individual. Another reason to collect large volume of urine for metabolomic analyses is that many important metabolites could exist at very low concentrations. Apparently, it is desirable to extract the metabolites from the liquid urine samples to enrich the analytes and make sample handling easier. In this section, I describe a porous extraction paddle
(PEP) developed by us for extracting metabolites from liquid urine. This is the first step of our sample preparation method development and is critical for the success of MALDI MS analysis of urine metabolome.
3-2.1. The PEP with solid phase extraction adsorbents
The PEP is constructed with a nylon bag immobilized in a flat woven stainless-steel cage which is fixed on a motorized stirring shaft. (Figure 21) The nylon bag of PEP can be filled with various solid phase extraction adsorbents. The PEP has a black lid that fit the half gallon jar used for urine collection. Once installed in the urine jar, the PEP is connected to a motor and starts to stir in the urine. Urine metabolites will be gradually absorbed onto the adsorbent particles in the nylon bag. We have used a mixed particulate
Page 64 of 133 adsorbent (MP-adsorbent) for PEP extraction.
The MP adsorbent consists of equal amounts of six adsorbents listed in Table 13. The constituent adsorbents cover most common chemistry for solid phase extraction. The octadecyl group binds nonpolar molecules. The phenyl group interact with aromatic compound through π- π stacking. Figure 21. The porous extraction paddle (PEP) having the The sulfonate and amine groups are cation and following components from top to bottom: stirring motor; four off-sets (vertical white rods), black lid (for a 0.5 anion exchanger respectively. Hydrophilic- gallon jar, not shown); shaft; horizontal PTFE bar into which the shaft is press-fitted at the top of the bar, with a slot on the lower side that accommodates the cage, and modified polymer retains polar molecules, and with two vertical slots for two Tiewraps; porous nylon bag (6.0 × 6.5 cm) containing 2 g of MP-adsorbent that the poly amide resin selects semi-polar analytes. is sandwiched between two sheets of stainless steel mesh (each 8.0 × 8.7 cm), where the meshes are held together further with three additional Tiewraps.
Mean Adsorbent Functional Group Type of Binding Particle Size (μm) Silica-octadecyl Reverse phase 50
Silica-phenyl
Aromatic ring 50
Silica-ethylphenyl sulfonate Cation exchange 50
Silica-propyltrimethylamine Anion exchange 50
Hydrophilic-Modified Styrene N/A Polymer Mixed 55-60
Polyamide Resin N/A Mixed 50-160
Table 13. The six adsorbents used to make the MP-PEP. All adsorbents were purchased from Supelco (Bellefante, PA, USA).
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3-2.2. Evaluation of extraction efficiency of various PEP with a standard dye
To evaluate the adsorption efficiency of the MP-PEP, we tested it for removing the Malachite Green
dye from an aqueous solution acidified with 4% acetic acid. Malachite Green is chosen as a model
compound since it is an economic industrial dye that is
commercially available, easy to detect, and has aromatic
and hydrophobic groups (Figure 22) resembling that of
many xenobiotic pollutants and drugs. The acidification
by acetic acid was used as a preserving method during
urine sample collection. Figure 22. The structure of Malachite Green dye.
We first tested a small size “mini MP-PEP” in a 2-mL vial of dye solution by visual inspection.
Figure 23 shows that the dye solution became visually clear after shaking at 230 oscillations per minute.
The originally white PEP bag turned blue after incubation. Then, we quantitatively evaluate the adsorption
kinetics of the regular size PEP with 2-g MP adsorbent in 1.8-L dye solution. The concentration of
Malachite Green in solution was monitored by visible light absorbance at 617 nm. The PEP was stirred at
190 rpm. Three MP-PEP were tested to evaluate standard deviation of adsorption. The same experiment
was also conducted with two other types of PEP for comparison. One PEP contains Carboxen-1003
Figure 23. A vial containing Malachite Green Figure 24. Absorbance of Malachite Green dye in a 4% acetic acid dye with a mini-PEP at (A) time = 0 and (B) time solution during extraction using a PEP packed with (A) an Empore = 8 minutes after shaking at 230 oscillation rate. SDB-XC membrane , (B) 2.0-g MP-absorbent (n =3), (C) 2.0-g Carboxen-1003 absorbent.
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(Supelco), a carbon molecular sieve, and the other contains an Empore SDB-XC (polystyrene divinylbenzene) membrane. The residual concentrations of Malachite Green dye were monitored over time during PEP extraction. (Figure 24) In Figure 24, we observed that dye extraction with Carboxen PEP adsorption is fastest while the SDB-XC membrane PEP is slowest. The adsorption kinetics of individual
MP-PEP bags has substantial variation, possibly caused by variation in particle size which in turn could block the pores in the bag differently. However, at the end-point after 1day extraction, all PEP bags completely removed the dye from the solution. Therefore, for urine sample collection, we extracted the liquid urine samples with MP-PEP for 30 hours.
3-2.3. PEP extraction of urine samples for qualitative analysis of metabolites
To examine the extraction of urine metabolites using MP-PEP, we conducted MALDI-MS analysis directly on the recovered urine sample. The purpose of this experiment is to evaluate the overall efficiency of metabolite extraction using MP-PEP. The optimized sample preparation and high LC-MS method will be discussed in section 3-3. For MALDI-MS, 5-mg MP-adsorbent particles were taken from a urine- exposed PEP. The metabolites were eluted by 200-μL 40% acetonitrile in water with 20-mM triethylammonium acetate. The eluted supernatant was mixed with CCA matrix and subjected to MALDI
MS analysis. Figure 25 shows the spectra of the recovered urine sample and the control sample of blank
CCA matrix. The urine sample spectrum (Figure 25A) has many peaks in addition to that of the CCA matrix
(Figure 25B), corresponding to detected metabolites. The zoom-in spectra in the inset shows even more low intensity metabolite peaks were detected. Therefore, we confirmed that the MP-PEP was able to extract a large number of metabolites from urine. Due to the possible mutual interference and suppression between metabolites, we had to develop LC-MS method as described in section 3-3 to reduce the complexity of the
MS spectra.
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Figure 25. MALDI MS spectra of (A) eluates from urine-exposed PEP, and (B) CCA matrix blank. The insets are the low-mass region of the spectra zoomed in 25 times to show the low intensity peaks.
Here, we submitted several high intensity peaks to MS/MS analysis of fragments to demonstrate detection of known metabolites. The MS/MS spectra of these metabolites were elucidated as below.
Combining the accurate MS of the selected precursor ion and the pattern of product ions of fragments, we tentatively matched the detected metabolites to a sulfate, glucuronide double conjugate of apigenin/genistein (Figure 26), uric acid (Figure 27), vitamin B1 (Figure 28), and 2,3-dioctanylglyceramide
(Figure 29). In addition, we also detected some peptide like the one shown in Figure 30 using the software
DeNovo Explorer (Applied Biosystems, Framingham, MA). This qualitative analysis demonstrated that the
MP-PEP can extract various urine metabolites of very different properties.
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Figure 26. The MALDI MS/MS spectrum of the m/z = 525.030 peak in the MS spectrum. The accurate mass of precursor ion and the pattern of product ions match a sulfate, glucuronide double conjugate of apigenin/genistein.
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Figure 27. The MALDI MS/MS spectrum of the m/z = 169.035 peak in the MS spectrum. The accurate mass of precursor ion and the pattern of product ions match uric acid.
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Figure 28. The MALDI MS/MS spectrum of the m/z = 265.110 peak in the MS spectrum. The accurate mass of precursor ion and the pattern of product ions match vitamin B1.
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Figure 29. The MALDI MS/MS spectrum of the m/z = 358.264 peak in the MS spectrum. The accurate mass of precursor ion and the pattern of product ions match 2,3-dioctanoylglyceramide.
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Figure 30. (A) The MALDI MS/MS spectrum of the m/z = 1734 peak in the MS spectrum. The accurate mass of precursor ion and the pattern of product ions match a peptide with sequence AKVGEAKVMIIIDSME, which is derived from kinesin light chain. (B) The peptide sequence was annoted using the DeNovo Explorer software.
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3-2.4. PEP extraction of urine samples for quantitative analysis of targeted metabolites
To evaluate MP-PEP extraction performance quantitatively, we used three standard compounds, thiamine-d3, L-carnitine (O-octanyl[N-methyl-d3 HCl]), and reserpine to spike the urine sample. The three compounds have function groups ubiquitous in metabolites, (Figure 31) and could be used to represent the
thiamine-d3
L-carnitine Reserpine
Figure 31. The three compounds used to spike the urine sample for evaluating MP-PEP extraction and MALDI MS analysis. properties of many common classes of metabolites. In our experiments, certain amount of the standards was added to 1.8-L urine which was then subjected to the MP-PEP extraction procedure as described above.
All three compounds were detected in the spiked urine sample but not in the nonspiked urine control (Figure
32 and 33). The recovery yield of PEP extraction was quantified by a method of standard addition.
Specifically, two spiked urine samples were prepared. The first one was spiked with 400 nmol of each standard molecule before PEP extraction, and the MS spectra of recovered metabolites were shown in
Figure 32A and 33A. The MS peak intensities were normalized with respect to the endogenous 9-decenyl carnitine. The second sample was spiked in the same way before PEP extraction and subjected to a second
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140 fmol spike of each standards after PEP extraction per MALDI spot. The MS spectra were shown in
Figure 32B and 33B. Using the peak height for the standards in the singly spiked sample, HA, and the doubly spike sample, HB, the amount of standard recovered from PEP extraction in each MALDI spot can be determined: nA = HA/(HB‒ HA) ×140 fmol. Since the original amount of added standard is known nA0=
400nmol × 5 mg/ 2g × 1μL/ 0.2mL× 0.7μL/ 10μ L = 350 fmol, the recovery yield of PEP extraction for each compound can be calculated: Yield% = nA / 350 fmol × 100%. The measurement of yield was repeated three time. Thereby, we determined the recovery yields are 26±3.8% for thiamine-d3, 15±1.9% for L- carnitine (O-octanyl[N-methyl-d3 HCl]), and 52±3.3% for reserpine.
Figure 32. The MALDI MS spectra of the PEP-extracted urine samples (A) spiked with 400-nmol of each thiamine-d3, O-octanyl[N-methyl-d3] carnitine, and reserpine; (B) similarly spiked sample as (A) but with additional 140-fmol of the three compounds added to each spot on the MALDI sample plate. The labeled peaks are assigned to: 1, thiamine; 2, thiamine-d3; 3, O-octanoly carnitine; 4, O-octanyl[N-methyl-d3] carnitine; 5, nonanoyl carnitine; 6, decatrienoyl carnitine; 7, decenoly cartnitine; 8, decanoly carnitine. The inset is the nonspiked urine.
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Figure 33. The MALDI MS spectra of the PEP-extracted urine samples (A) spiked with 400-nmol of each thiamine-d3, O-octanyl[N-methyl-d3] carnitine, and reserpine; (B) similarly spiked sample as (A) but with additional 140-fmol of the three compounds added to each spot on the MALDI sample plate; (C) nonspiked. The peaks m/z = 609.280, 610.285, and 611.289 are respectively assigned to protonated reserpine and two isotopic reserpine.
We note that recovery yield of PEP extraction varies with metabolite properties. The O-octanyl[N- methyl-d3] carnitine has the lowest recovery yield, which can be explained by competitive binding of the endogenous carnitine compounds to MP-PEP during the extraction. Reserpine has the highest recovery yield suggesting that MP-PEP may work better on extracting molecules with large nonpolar structural elements. Since many pesticides, herbicides and drug metabolites have large nonpolar moiety, MP-PEP is suitable for xenobiotics extraction.
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3-3. Optimized procedure for UHPLC-MALDI MS analysis of urine metabolites
In the sections 3-3 and 3-4 of my dissertation work, we demonstrate the usefulness of UHPLC-
MALDI MS method for nontarget metabolomic analysis of underivatized urine sample. One major challenge in nontargeted metabolomic study is to detect the large number of the metabolites present in the urine samples at broad range of concentration. The intrinsic high sensitivity of MS spectrometry and the high separation resolution of UHPLC make them suitable techniques for meeting this challenge. Compared to other commonly used analytical platforms for urine metabolome analysis, MS has much higher sensitivity than NMR, and LC-MS has better recovery than GC-MS for less-volatile metabolites in urine.
Indeed, the previous studies reported discovery of dozens of metabolites in human urine using LC-ESI MS methods. In our method, we employed MALDI MS instead of ESI MS. In general, new techniques are useful for expanding the repertoire of detectable metabolites in nontargeted analysis. This is especially beneficial for detection of less-polar molecules by LC-MS methods. Although LC-MS allows detection of nonvolatile molecules, its application in less polar compounds is generally limited due to the poor ionization.
The ionization mechanisms of MALDI MS and ESI MS are very different. The ionization efficiency of these two techniques can be complementary to each other, and thus increase the number of detectable metabolites in urine. Moreover, in MALDI MS experiment, ionization and sensitivity can be optimized by adjusting the laser power.
To use UHPLC-MALDI MS for urine analysis, a key factor to success is proper sample preparation.
A suitable sample preparation strategy needs to be developed to remove salts and separate the complex metabolite matrix of urine samples. This sample preparation method should be highly reproducible for different experimental run at different time. We have set up and optimized a reliable sample preparation procedure consisting of sequential exaction and separation steps as described below.
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3-3.1. Our urine sample preparation strategy for LC/MALDI MS analysis
The analytical scheme of our UHPLC-MALDI analysis of urine samples is illustrated in Figure
34. Our workflow consists of two stages: (1) sample collection and extraction (steps 1-4 in Figure 34); (2)
LC separation and MS analysis (steps 5 and 6).
Figure 34. The workflow of our analysis of urine sulfateome.
In the first stage, a large amount of the first-morning urine samples is collected by the human subject at home every day for one week using a 2L jar with acetic acid preservative. This collection procedure not only provides sufficient sample for increasing the detectable metabolome, but also reduces the temporal variation of the metabolome and serves as a better representation of the average urine metabolome for the individual participants. In the step 1 of sample preparation, a porous extraction paddle
(PEP) made of six sorbents is used to extract the metabolite molecules from the large volume of liquid urine samples. For each 1.8L liquid urine, 2 grams PEP sorbents were used for extraction. The PEP extraction of urine samples allows enrichment of the metabolites and makes transportation and storage much easier. After
Page 78 of 133 urine extraction, the PEP sorbents appear to be yellow. The urine samples stored on the PEPs are shipped to the analytical lab and stored at ‒80°C.
For each analytical experiment, a 30-mg aliquot of the 2-g sorbents is used for the step 2 in Figure
34. The absorbed molecules are eluted by two 0.1M triethylammonium acetate (TEAA) buffer: first in 0.5- mL 30:70 ACN:H2O solution, and then in 0.5-mL 80:20 ACN:H2O solution. After each elution step, the sample is centrifuged. The two supernatants are combined. High metabolite recovery of the two-step elution was confirmed by the facts that the yellow color of sorbent particles disappeared after elution, and a second round of elution only produced extracts with UV absorbance lower than 1% of that from the first round of elution. The high recovery of elution is important for ensuring high sensitivity and reproducibility of the subsequent UHPLC-MALDI analysis.
The eluted supernatant is then diluted with water and subjected to a solid phase extraction (SPE) column with weak anion exchanger polymer resin. We selected weak anion exchanger SPE since our study was focused on the discovery of sulfate conjugated metabolites. Other types of SPE resin, such as cation exchanger, reverse phase, and hydrophilic interaction, are available for separation based on other molecular properties. In fact, for comprehensive metabolome discovery, it is recommended to conduct several parallel
UHPLC-MS analyses using SPE columns with different selectivity. Another important consideration for selecting SPE column is the binding and elution solutions. Before loading to the weak anion exchange column, the solution from step 3 was diluted with water to increase binding of the anionic metabolites with large nonpolar moiety. Then, the column was washed by 20 column volumes of 25-mM ammonium acetate and 20 column volumes of methanol. This washing step removes moderately bound molecules. To elute the highly nonpolar anionic metabolites of interest, 10 column volumes of 5% ammonium hydroxide in 50% methanol aqueous solution was used. Ammonium hydroxide deprotonates the weak anion exchanger and thus neutralizes its positive charges. Note that only volatile buffer salt (ammonium acetate) and base
(ammonium hydroxide) are suitable for washing and elution, because they will decompose during the ionization process in MS spectrometer. Nonvolatile salts, such as sodium phosphate, can strongly decrease
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MS signals by ion suppression and formation of multiple analyte-salt adducts. Therefore, our SPE mobile phase conditions were also designed to increase selectivity and reproducibility. After the sample preparation steps 1-4 in Figure 34, the urine samples are ready for analysis in the step 5 (UHPLC separation) and step
6 (MALDI MS).
3-3.2. High reproducibility of our sample preparation strategy
To ensure the reliability of our analytical scheme, we evaluated the reproducibility of our sample preparation strategy by UHPLC-UV experiments. Following the step 1-4 in Figure 34, we prepared a urine sample (designated as urine E in our study). 5-μL of the urine sample was injected to a capillary C18 reverse phase UHPLC column with UV detection. The UHPLC experiment was repeated three times with the same urine samples. The chromatograms of the three runs shown in Figure 35 have essentially identical pattern.
This result elucidates the high similarity of UHPLC experiments at different run.
To examine the reproducibility of our sample preparation method, we repeated step 1-5 in Figure
34 six weeks after the initial experiment. Different aliquots were taken six weeks apart from the same urine
PEP sample stored at ‒80 °C. In these two runs, UHPLC was also coupled with a robotic MALDI plate spotter. A slow elution over 100 minutes was used and the fraction droplets were spotted to the MALDI plate every 20 seconds. The UV chromatograms of the two runs six weeks apart appear to highly overlap with each other as shown in Figure 36. The MALDI spectra at a given spot on the plate were also aligned very well.
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Figure 35. UHPLC chromatograms of three successive injection of the urine sample E. The chromatograms are shifted vertically for clear comparison.
Figure 36. UHPLC chromatograms of the urine sample E prepared by the step 1-5 in Figure 34 at time 0 (curve 1) and 6 weeks later (curve 2. The chromatograms are shifted vertically for clear comparison.
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As described above, we conclude that our sample preparation method and analytical scheme give highly consistent data. We attribute this to the design of the method along with great care in the conditions, especially precisely defined, slow elution steps to mimic equilibrium conditions.
3-4. UHPLC-MALDI analysis of sulfatome and glucuronidome of urine samples
With a sample preparation and analytical method established, we then analyzed the metabolome of urine samples by UHPLC-MALDI MS. Since our main goal was to develop and validate the analytical method, we focused on two important classes of metabolites, i.e., sulfate and glucuronide conjugates. These conjugate metabolites are collectively referred as sulfatome and glucuronidome, respectively. As shown in
Figure 3, sulfate and glucuronide conjugations are two major pathways in the phase II metabolism of nonpolar molecules. Therefore, sulfateome and glucuronideome apparently encompass a large portion of the total urine metabolome. In the MS/MS analysis, the conjugated metabolites can be identified by the characteristic fragments related to the sulfate and glucuronide conjugates. For general urine metabolome studies, the sample preparation and analytical methods described in this dissertation work could be extended to analyze other types of metabolite conjugates.
3-4.1. UHPLC-UV spectra of 6 urine samples
Using the sample preparation steps 1-4 described above, we prepared urine samples from six pregnant women in Puerto Rico. The urine samples are designated as A, B, C, D, E, and F. The results of urine metabolome analysis may shed light on the women’s health and pollution issues in Puerto Rico where the preterm birth rate is much higher than many states of the main-land US. A 5-μL of each urine extract was injected to the C18 UHPLC column and eluted with a 10% to 80% acetonitrile aqueous solution gradient over 100 minutes. The UHPLC UV chromatograms were taken at three different wavelength 260 nm, 216 nm and 320 nm. (Figure 37). The chromatograms consist of many narrow peaks indicating high resolution of separation. The six urine samples have similar overall pattern of chromatograms, which
Page 82 of 133 reflects some similarity of urine composition between different individuals. On the other hand, the specific
Figure 37. UHPLC chromatograms at 260 nm, 214 nm and 320nm of six urine sample prepared by the sample preparation step 1-5 in Figure 34.
Page 83 of 133 details of the chromatograms vary from sample to sample showing the variation in individual urine metabolic profile due to difference in diet, health condition, pollutant exposure, etc.
The high-resolution separation of metabolites by UHPLC is important for increasing the sensitivity of subsequent MS experiments and simplifying MS spectrum analysis. The eluates at a flow rate 4 μL/min were spotted to a MALDI sample plate every 20s per drop (spot) by a robotic microfraction collector. Each of the MALDI plate have 220 eluate spots. 0.5-μL 5 g/L CCA matrix in 50% acetonitrile aqueous solution with 7mM ammonium phosphate dibasic (suppresses salt adducts) were added to each spot on the sample plate. After drying in air, the metabolites in the eluate droplets cocrystallized with the CCA and were subjected to MALDI MS MS/MS experiments as described in following sections.
3-4.2. Sulfatome and glucuronideome of six urine samples detected by UHPLC-MALDI MS
The MS spectrum of each eluate fraction spot collected from UHPLC were obtained by a MALDI
TOF MS spectrometer in negative ion mode. 220 MS spectra at different UHPLC retention time were obtained for each of the six urine samples, which gave 1320 MS spectra in total. The metabolite MS peaks were autodetected by a set of selection rule: (1) only the peaks with S/N> 20 were selected to reject the signals from matrix molecules; (2) up to 100 highest peaks with in each MS spectrum; (3) peaks with the same m/z from neighboring spots were only recorded once because the UHPLC peaks usually spread over
2-3 spots. For each of the six urine samples, ~1800 ion peaks were selected from the MS spectra. Many ion peaks with the same m/z and LC retention time (spot number) appear in more than one urine samples. This is consistent with the similar overall patterns of the chromatograms and the similarity of the chemical compositions of individual urine metabolome. In our study, we mainly focus on method development for urine metabolome discovery. Therefore, the detected metabolites from the six urine samples were combined for further identity analysis. The same data can be expanded in future for differential studies of individual urine metabolome when statistically significant numbers of urine samples are available.
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To further analyze the identity of the detected metabolites in the MS spectra, each MS peak was subjected to a MS/MS measurement to generate a corresponding MS/MS fragment spectrum. It is impractical to manually analyze all 6 x 1800 MS/MS spectra and reconstruct the molecular structures of the metabolites from the fragment pattern. However, the sulfate and glucuronide conjugated metabolites can be automatically detected by the Peak Explore software based on the corresponding characteristic fragment peaks in the MS/MS spectra. Fragmentation of sulfate conjugates can produce two characteristic peaks in MS/MS spectra: (1) a product ion of the precursor ion after loss of SO3 with m/z (M‒1) ‒80; (2)
‒ the product ion of HSO4 . If either or both of these product ions are detected in a MS/MS spectrum with
S/N>4, the corresponding metabolite is considered as a sulfate conjugate. It is important note that our high-
‒ ‒ resolution MS/MS spectra allow differentiation between the isobaric HSO4 and H2PO4 Ions. If phosphate conjugates are of interest, two product ions with m/z = 79 (dominant) and m/z = 97 can be used as benchmarks for identification. Hence, the absence of the m/z = 79 in MS/MS spectra serves as another criterion for sulfate detection. Based on the presence of neutral loss of 80 or formation of product ion m/z
97, we have discovered totally 1129 unique sulfate conjugates that have distinct m/z of precursor ion and
LC retention time. The full list of molar masses (M‒1) of these sulfate conjugates ranging is included in the Table S1 in the Supporting Information of reference (205). Due to the existence of isomers with similar structures, the number of total sulfate conjugates from the six urine samples is expected to be even larger.
The numbers of sulfate conjugates detected for individual urine sample range from 549 to 711 with an average of 618 and a standard deviation of 71 (Table 14). This observation suggests that the urine metabolome varies substantially person to person. It is also interesting to compare our results to previously reported nontargeted urine sulfateome study using UHPLC-ESI MS MS/MS.(206) In their study they only discovered 15 sulfates in one urine sample in a single procedure. By comparing the analytical schemes, the superior results obtained in our study may be attributed mainly to sample enrichment of large samples by
PEP, pre-selection by weak anion exchange SPE, and high resolution of the TOF MS analyzer.
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Sulfates Glucuronides Double Conjugates Urine (M-1)-80 m/z 97 Total (M-1)-176
A 424 325 629 94 47
B 275 353 550 49 28
C 350 324 549 105 54
D 392 286 576 57 27
E 398 451 711 81 38
F 332 475 691 86 43
Table 14. The number of putative sulfate and glucuronide conjugated metabolites in the sixurine sample discovered by our UHPLC MALDI MS and MS/MS analysis. Therefore, our method provides a promising analytical platform for future urine nontargeted, highly nonpolar metabolomic studies.
In addition to sulfate conjugates, we also discovered some glucuronide metabolites by searching for the characteristic product ion M‒1‒176 in the MS/MS spectra. The numbers of detected glucuronides are much lower than the sulfates. (Table 14) This might be caused by lower binding of glucuronides to the weak anion exchange SPE and lower ionization of glucuronides in the negative ion mode of MS as compared to sulfates. Therefore, we expect the detection of glucuronides could be improved by modifying our method that is originally developed for sulfate detection. Specifically, other SPE columns and positive ion mode of MS can be used. Admittedly, analytical methods should always be optimized for the specific type of analytes under study. Since our goal is to develop new analytical scheme of general use, we will leave the specific modification of method for glucuronide to future study. In the following sections, we will focus on further identification of the detected sulfate conjugates.
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3-4.3. Tentative assignment of the sulfate conjugates by matching METLIN database
In nontargeted analysis, the identity of detected metabolites is usually determined by comparing
the measured properties to the values in the databases. To confidently identify a molecule without prior
knowledge of the analyte, it usually requires matching database values of three orthogonal quantities, e.g.
LC retention time, exact mass of precursor ion, and fragment pattern in MS/MS spectrum. However,
compared to GC-MS databases, LC retention time and MALDI MS/MS spectra are much more difficult to
Figure 38. Evaluation of the 1129 precursor ions detected in the UHPLC-MALDI MS analysis of the sixurine sample. The putative identity of the precursor ions was determined by searching their experimental exact masses in the metabolite database METLIN. Marched compounds are designated as “hit”.
Page 87 of 133 standardize and archive. Therefore, we could not make the definitive identification of the 1129 sulfate conjugates detected in our experiments. However, the high resolution of our TOF MS (~3ppm) allow us to determine the putative identity of these sulfate with reasonably high confidence. We have estimated the identity of the metabolite precursor ions by three ways. Our strategy and results of identity estimation for the detected metabolites are summarized in Figure 38.
First, we match the exact mass of the 1129 precursor ions to the [M‒H]‒ values in the metabolite database. One useful metabolite database is METLIN created and maintained by Scripts Research Institute.
Currently, METLIN contains 961,829 molecules including lipid, steroids, small peptides, carbohydrates, central carbon metabolites, plants and bacteria metabolites, pharmaceutical and environmental metabolites, toxicants, etc. METLIN also have a big collection of experimental qTOF MS/MS data obtained at various collision energies, different ionization modes, and using different instruments (SCIEX, Agilent, Bruker, and Waters). In addition, 200,000 metabolites in METLIN has in silico (computer simulated) MS/MS data.
Our MS/MS data were measured by TOF-TOF instrument and cannot be directly compared to those qTOF data. Therefore, we simply searched the experimental exact mass of the [M‒H]‒ in METLIN. Due to the existence of isomers, the same accurate mass can generate hundreds of metabolite hits in METLIN. The high resolution of our TOF MS helped to reduce the number of hits. After we imposed the condition of being sulfates, only 150 hits of sulfate conjugated metabolites were identified for the 1129 precursor ions.
(Table S2 in the Supporting Information of reference (205)) Among these identified sulfates, 27 are steroids and 59 hits are flavonoids. Steroids are important endogenous metabolites from lipid membrane
Page 88 of 133 components and hormones. Flavonoids is a class of common diet metabolites from plants such as blueberries, black tea, and red wines. (Figure 39)
With high-resolution MS spectra and the sulfate characteristic MS/MS ions, the tentative identification of the sulfate metabolites using METLIN hits sometimes is reasonably confident. For example, the MS and MS/MS spectra of three identified metabolites are described in more details in 3-4-4.
If further investigation is needed, the putative identity of metabolites can be readily confirmed in targeted
LC-MS and MS/MS analysis using the standard compounds. The majority of the 1129 detected sulfates did not match any hit in METLIN, most likely because METLIN deposits less sulfate conjugated metabolites than the unconjugated ones. To gain further information of the detected sulfate metabolites, we deduced their unconjugated precursor according to the chemistry of the phase I and II metabolisms. This excise is
The 17-C backbone of steroid The 15-C backbone of flavonoid
Figure 39. The molecular backbone of steroids and flavonoids. represented by the other two identification pathways in Figure 38.
Starting from the conjugated metabolites, we first infer their structure before the phase II metabolism. Without the sulfate conjugation, the metabolites are present as alcohols (R‒OH) with the mass differ from sulfate by ‒SO3+H. Since METLIN has more positive ionization mode data than the negative ionization mode data, we converted our sulfate conjugated precursor ions [M‒H]‒ (m/z) in negative mode
+ to the corresponding positive ion of unconjugated alcohol [M+H‒SO3] (m/z +2‒80). By searching m/z ‒
78 in positive ionization mode of METLIN, we found 6727 hits. The considerably increased number of
Page 89 of 133 matched hits is due to the substantial larger data for unconjugated alcohols in positive ionization mode than that of the sulfated metabolites in negative ionization mode. On average, each detected precursor ion corresponds to six hits of isomers in METLIN. These isomers often can be differentiated by their MS/MS fragment spectra. Therefore, further analysis of the MS/MS spectra obtained in our experiments and/or new experiments on the standard compounds could provide more definitive information about the molecular structure and identity of the metabolite of interest. Since our goal is method development and validation for nontarget analysis, the detailed targeted analysis is beyond the scope of our study. Amongst the 6727 hits of alcohol metabolites, there are 122 hits of steroids (Table S5 in the Supporting Information of reference
(205)) and 1582 hits of flavonoids (Table S7 in the Supporting Information of reference (205)). The 122 matched steroids are various derivatives of the 20 common human steroids listed in Table S4 in the
Supporting Information of reference (205), and therefore can be expected to be detected in human urine samples. Flavonoids are common metabolites in plants and fungi. The plant and fungus metabolomes were extensively studied, and the data deposited in METLIN are expected to contain many isomers.
Similarly, we also explored the possible identities of the metabolite precursors before the phase I metabolism of the detected sulfate conjugates. During the phase I metabolism, many nonpolar metabolites are oxidized to more polar alcohol molecules which later undergo various conjugations in phase II metabolism. Therefore, this approach of removing sulfate and oxygen from the detected ions is particularly useful for putative identification of nonpolar xenobiotics. For each final sulfate ion [M‒H]‒ (m/z), we
+ searched the ion [M+H‒OSO3] (m/z +2‒96) in the positive ionization mode in METLIN. This search resulted in 6156 hits in METLIN. Since many environment pollutants that adversely affect human health are nonpolar xenobiotics, we further examined these matched hits and found 45 hits of pollutants as discussed in more details in section 3-4-5.
3-4.4. Examples of sulfated metabolites discovered in urine samples by MALDI MS MS/MS
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In this section, we show three examples of sulfated metabolites discovered in urine samples. These metabolites are xenobiotics and endogenous hormones that are associated with human health. Figure 40a shows the MALDI MS spectrum of an UHPLC fraction of a urine sample. Figure 40b shows the MS/MS spectrum of the strongest peak, [M‒H]‒ m/z = 364.086, in the MS spectrum. The MS/MS spectrum has two
‒ ‒ product ions: m/z = 80 corresponding to SO3 fragment and m/z = 284 corresponding to [M‒H‒SO3] .
Therefore, we postulate the m/z = 364.086 peak is a sulfate conjugated metabolite. We searched METLIN in negative ionization mode MS for m/z = 364.086 with accuracy of 3ppm, i.e., m/z = 364.086 ± 0.001, and found a hit of morphine sulfate with exact mass 364.085. Morphine is an opioid pain medication with many
Figure 40. Detection of morphine-3-sulfate by the UHPLC-MALDI analysis. (a) Detection of the precursor ion as M‒1 at m/z = 364.086 with accuracy of 3 ppm (indicated by the blue arrow) in MALDI MS spectrum. (b) Detection and assignment of the two product ions of putative morphine-3- sulfate (m/z = 80 and 284) in the MALDI MS/MS spectrum.
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Figure 41. Detection of 3β,16α-dihydroxyandrostenone sulfate by the UHPLC-MALDI analysis. (a) Detection of the precursor ion as M‒1 at m/z = 383.151 with accuracy of 5 ppm (indicated by the blue arrow) in MALDI MS spectrum. (b) Detection and assignment of the three product ions of 3β,16α-dihydroxyandrostenone sulfate (m/z = 80, 97 and 303) in the MALDI MS/MS spectrum. strong side effects and a high potential of addition. Chronic use of morphine by pregnant women has a high risk to cause the newborns to have opiate withdrawal symptoms.
Another important metabolite discovered in our study is dihydroxy-androstenone sulfate. Figure
41a shows the MALDI MS spectrum of the UHPLC fraction containing this metabolite, the peak at m/z =
383.151. It is believed to be a sulfate conjugate because its MS/MS spectrum in Figure 41b has three
‒ characteristic product peaks. The m/z = 80 peak corresponds to the SO3 fragment, and the m/z = 97 peak
‒ ‒ corresponds to the HSO4 , and the alkoxylate fragment [M‒H‒SO3] m/z = 303. It is interesting to note that
‒ the HSO4 fragment has not been seen in the MS/MS spectrum of morphine. This is consistent with expectation that the oxygen-carbon bond in the phenolic group of morphine is more difficult to break than
Page 92 of 133 that in the alkoxyl group of dihydroxy-androstenone. By searching for the anions m/z = 383.151 ± 0.002 (5 ppm) in METLIN, we assigned this peak to dihydroxy-androstenone with exact mass m/z = 383.153. In fact, 3β,16α-dihydroxyandrostenone sulfate is a normal human steroid hormone metabolite in placenta and breast milk of women in pregnancy and lactation. The maternal 3β,16α-dihydroxyandrostenone sulfate level is a biomarker directly correlated to the newborn adrenal gland development. (207)
We also apparently detected the conjugated metabolite of the female sex hormone, estriol. This conjugate is a double-conjugates. Figure 42a shows the precursor ion of this metabolite, m/z = 543.151, detected in the MS spectrum. The MS/MS of this MS peak is given in Figure 42b. Besides the typical sulfate
Figure 42. Detection of estriol-3-sulfate-16-glucuronide by the UHPLC-MALDI analysis. (a) Detection of the precursor ion as M‒1 at m/z = 543.151 with accuracy of 5 ppm (indicated by the blue arrow) in MALDI MS spectrum. (b) Detection and assignment of the three product ions of estriol-3-sulfate-16-glucuronide (m/z = 80, 463 and 367) in the MALDI MS/MS spectrum.
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‒ ‒ fragment peaks, SO3 m/z = 80 and [M‒SO3] m/z = 463, we also observed a strong product peak at m/z =
367 in the MS/MS spectrum. This product peak corresponds to a neutral loss of 176 which is characteristic for glucuronide conjugates. In METLIN negative ionization mode, there is one double conjugated metabolite, estriol-3-sulfate-16-glucuronide, having exact mass 543.154 matches the measured accurate mass 543.151± 0.003 (5 ppm). The detection of fragments for sulfate and glucuronide further increases the confidence of the identify of this metabolite. Estriol is one of the three common human endogenous estrogens. During pregnancy, the estriol production in women increases about 1000 times. Low level of free estriol may indicate genetic disorder of the fetus such as Down syndrome. Estriol test is part of the antenatal screening for genetic defects of fetus.
3-4.5. Candidate pollutants in the 6 urine samples
In the section 3-4-4, we have explored how to deduce the identity of metabolite conjugates using their experimental MS and MS/MS spectra. This analysis is greatly limited by the data availability of sulfate conjugates in the database like METLIN. With the assumption that the sulfated metabolites arose from the common phase I and II metabolism, we searched the unconjugated and unoxidized metabolites [M+H‒
+ OSO3] (m/z ‒93.937) in METLIN and found 6156 matched hits. Despite the redundant hits of isomers, this analysis still significantly narrows down the possible choices of identity (on average 5 candidates for
Herbicide Pesticide Priority pollutant
benzofenap benomyl bis(2-ethylhexyl) phthalate
butralin cinmethylin di-n-octyl phthalate
cinmethylin dinitramine indeno (1,2,3-cd) pyrene
clethodim dinoseb naphthalene
dinitramine ethofumesate anthracene
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dinoseb flumetralin phenanthrene
dinoterb imazethapyr
ethofumesate isopropalin
imazethapyr methiocarb
isopropalin metolachlor
mefenacet myclobutanil
metolachlor napropamide
napropamide oxadiazon
oxadiazon pirimiphos-ethyl
prosulfocarb sethoxydim
quizalofop thiobencarb
sethoxydim naphthalene
thiazopyr rotenone
thiobencarb
tralkoxydim
Table 15. The hits of pesticides, herbicides, and priority pollutants that may exist in the six urine samples discovered by searching METLIN as shown in Figure 38.
each metabolite) and thereby provides a useful guidance for further targeted studies. Many of the matched
hits are nonpolar pollutants. Using the keywords from lists of 334 pesticides,(208) 426 herbicides,(209) and
129 priority pollutants,(210) we have obtained 35 hits of pollutants listed in Table 15. To the best of our
knowledge, this is the first nontargeted analysis of environmental pollutants in urine. We have also
conducted similar analysis for the detected glucuronide conjugates but did not find any hits of pollutant. As
mentioned before, our analytical scheme has not been optimized for detecting glucuronides.
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Amongst the pollutants in Table 15, the two phthalates (Figure 43) have been associated with preterm birth in previous studies.(211, 212) Using the analytical platform of UHPLC MALDI MS MS/MS, one can examine the correlation between exposure of environmental pollutants and health conditions (e.g., preterm birth). To conduct such analysis, our method needs to be adapted along following lines. First, a large number of samples is needed to produce statistically significant results. Also, the xenobiotics-disease correlation study requires quantitative experiments. In targeted analysis, an authentic compound with known concentration can be used as internal standard for quantification. In nontarget analysis, one way to
bis(2-ethylhexyl) phthalate di-n-octyl phthalate
Figure 43. The phthalate pollutants that match the MS ions of the urine samples in our study.
Urine m/z = M‒1‒80 m/z =97 Sum A 8.8 3.6 12.4 B 4.4 3.0 7.4 C 6.7 3.2 9.9 D 8.8 2.7 11.5 E 10.2 8.6 18.8 F 9.5 9.5 19.0
Table 16. Total MALDI MS intensities (x10-5) of urine sulfates. conduct quantitative analysis is to normalize the intensity of individual peak by the total intensity of all sulfates in the urine samples. Table 16 shows that total sulfate levels in different urine samples are at the same order of magnitude. Finally, xenobiotics usually can exist in both conjugated forms and the free form in urine. To study its correlation with diseases, the total level of the xenobiotics of interest need to be quantified. Therefore, in-vitro deconjugation is often conducted to convert the conjugated form into
Page 96 of 133 unmodified xenobiotics so that the total concentration can be determined. The method for sulfate deconjugation and subsequent MS analysis are explored in the section 3-5.
3-5. Deconjugation and cationic tagging of urine samples for UHPLC-MALDI analysis
Many urine metabolites are found in conjugated forms. As discussed above, the conjugated group such as sulfate can help identification of the metabolites. However, natural conjugation of metabolites is often incomplete, i.e., both conjugated and free metabolites could be present in urine. The dispersion of metabolite species leads to decrease in MS sensitivity and makes quantification complicated. Therefore, in- vitro deconjugation of urine samples is commonly applied to convert the conjugated metabolites into their free form. In addition, subsequent chemical conjugation can be conducted to transform the metabolites of interest into a particular conjugated. This deconjugation-conjugation technique can be used to normalize the conjugated metabolites and facilitate LC-MS detection.
To achieve efficient deconjugation of urine metabolites, enzymatic reactions are usually employed.
For example, sulfatase is a class of enzymes that catalyze hydrolysis of sulfate esters into sulfate ion and alcohols/phenols. (Figure 44) A commercially available aryl sulfatase purified from Helix pornatia (Roman
Snail) has been used to deconjugate steroid sulfates in metabolic analysis.(213-215) The Helix pornatia sulfatase also has β-glucuronidase activity. Here, we will demonstrate the use of Helix pornatia sulfatase
O O sulfatase
OSO + H2O ROH+ HO S O
R O O
Figure 44. 4-sulfatase from human. X-ray structure from Protein Data Bank in Europe (PDBe: 1fsu). Sulfatase catalyzes hydrolysis of sulfate ester into sulfate and phenol or alcohol.
Page 97 of 133 for deconjugation of urine metabolites. We will optimize the conditions for this enzymatic reaction to maximize the yield of deconjugation. Following the deconjugation, we will conduct derivatization of the deconjugated urine sample using a cationic tag previously developed in our group. We will show the cationic tagging markedly increased the sensitivity of MALDI MS detection.
3-5.1. Optimization of conditions for enzymatic deconjugation of urine
We used the urine sample F to optimize the conditions for the sulfate deconjugation reaction catalyzed by Helix pornatia sulfatase. The urine sample was prepared using the method developed in section
3-3. Each 20- μL sample for deconjugation experiment contains approximately 0.5-μmol sulfate conjugates according to the estimation in section 3-4. We explored the enzymatic reaction at various pH (5.0, 6.0, and
7.0) and 37 °C for different incubation time (1 hour and 2 hours). After the reaction, 1-μL aliquot (originally containing ~25-nmol total sulfate conjugates) was subjected to negative ionization mode MALDI MS experiment to monitor the yield of deconjugation. The matrix peak at 351.001 was used as the internal standard for quantification. 11 urine sulfates were used to estimate the yield of reaction. The relative intensity of the detected sulfate peaks is defined as the ratio of the intensity of sulfate peak to that of the matrix peak. The results of sulfate intensity measured by MALDI MS are summarized in Figure 45. Based on the MS results in Figure 45, we have calculated the yield of deconjugation reaction under different reaction conditions for the 11 urine sulfate conjugates. (Figure 46)
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1 hour 3.5
3
2.5 control 2 pH 7 1.5 pH 6
Relative intensity 1 pH 5 0.5
0
m/z 2 hours 3
2.5
2 control 1.5 pH 7
Relative intensity 1 pH 6 pH 5 0.5
0
m/z
Figure 45. The relative intensity of 11 sulfate peaks detected by MALDI MS for the urine samples before and after enzymatic deconjugation reactions under different conditions. Control is the original urine sample prepared by the same procedure but without adding the enzyme.
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1 hour 100% 90% 80% 70% control 60% pH 7 50%
Reduction pH 6 40% pH 5 30% 20% 10% 0%
m/z
2 hour 100% 90% 80% 70% 60% control 50%
Reduction pH 7 40% pH 6 30% pH 5 20% 10% 0%
m/z
Figure 46. The yield of deconjugation of the 11 sulfate conjugates under different reaction conditions measured by MALDI MS.
Page 100 of 133
According to Figure 45, the enzymatic deconjugation reaction has highest yield at pH 5.0 and 37 °C with 1-hour reaction time. After the reaction, three sulfate metabolites were 100% deconjugated, three other sulfates were ~75% deconjugated, four sulfates were ~50% deconjugated, and one sulfate was 30% deconjugated. This result shows that the Helix pornatia sulfatase can catalyze deconjugation for all 11 sulfated metabolites. Since enzymatic reactions are usually highly selective, the variation of deconjugation yield for different substrates is expected. Despite of this variation, the degree of deconjugation for all sulfate analytes in this study is sufficient for conducting the subsequent ionic tagging which substantially increases the sensitivity of MS detection. For applications of targeted analysis, the extent of enzymatic deconjugation for the metabolite target can be calibrated with the authentic sulfate standard.
3-5.2. Cationic tagging of the deconjugated urine sample
After deconjugation reaction, we conducted a cationic derivatization of the urine metabolites to increase the sensitivity of MALDI MS detection. We have chosen to use cationic tagging instead of the anionic tagging described in section 3-1 because the detection of cationic tagged molecules in postive ionization mode MALDI MS is remarkably sensitive. The cationic tag used here has been developed in our lab by Dr. Poguang Wang et. al.(216) This tag molecule is N-(2-(Bromomethyl)benzyl)-N,N- diethylethanaminium bromide, designated by us as CAX-B (cationic xylyl-bromide). One unique advantage of CAX-B as a tagging agent is that it works efficiently for different types of analytes including alcohols,
Figure 47. Cationic tagging of various types of analytes using CAX-B.
Page 101 of 133 phenols, amines, and thiols. (Figure 47) Here, we used the CAX-B to tag the deconjugated urine sample for UHPLC MALDI MS analysis. The procedure for deconjugation and cationic tagging of urine sample is summarized in Figure 48.
Figure 48. The schematic work flow of deconjugation and cationic tagging of urine sample for UHPLC MALDI MS analysis.
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3-5.3. UHPLC MALDI MS analysis of cationic tagged urine sample
After cationic tagging, the urine sample was analyzed by UHPLC with a C18 column. The chromatogram monitored by UV absorbance at 260 nm is shown in Figure 49. A blank reaction mixture with 2 mg/mL CAX-B and 20 mg/mL triethylamine but without urine was run as a control. The chromatogram of the tagged urine sample shows rich features distinct from that of the control sample. This result indicates recovery of many metabolites after the deconjugation and ionic tagging reactions. The fractions of UHPLC elutes were collected on the MALDI sample plates and subjected to MALDI MS analysis.
Blank reaction control
Tagged urine sample
Figure 49. The UHPLC chromatograms of the cationic tagged urine sample (black trace) and the control of blank tagging reaction mixture without urine (blue trace). UV absorbance was monitored at 260 nm.
Page 103 of 133
MALDI MS spectra of the UHPLC fractions of the cationic tagged urine sample also show many peaks of precursor ions with high intensity. For example, Figure 50 shows the MS spectrum of the UHPLC fraction eluted at 42 minutes. The spectrum of the cationic tagged urine fraction has a very rich metabolite pattern. Note that, the UHPLC UV chromatogram in Figure 49 shows the metabolites in 42-minute fraction are less abundant than those in the earlier eluted fractions. The reason we have chosen the 42-minute fraction to show MS sensitivity is that the MS spectra of metabolite-rich fractions are overcrowded for a clear demonstration.
TOF/TOF™ Reflector Spec #1[BP = 212.0, 83935] 441.013 100 Blank reaction control 6.8E+ 90
80 443.013 70
60
50
% Intensity 393.217 40 445.036 30 401.075 423.054
20 396.118 568.134 656.065 462.996 399.047413.151 435.159 506.159 564.996 617.054 10 464.995 485.133 524.144 433.015447.427 543.015 574.951591.177 632.062 666.018 0 388.0 457.6 527.2 596.8 666.4 736.0 Mass (m/z) <<295>> TOF/TOF™ Reflector Spec #1=>MC[BP = 379.1, 52724] 458.324 100 3.3E+ 430.293 556.362 90 393.216 432.307 Tagged urine sample 700.466 80 446.324
70
60 651.463 443.012 50 572.387 460.335 506.347 % Intensity 395.231 426.263 448.338 558.382 40 478.348 530.373 434.321 652.465 456.312 504.362 576.414 612.450 30 472.323 528.359542.373 400.118 490.346 514.350 560.389 531.375546.380 653.474 401.071 461.341 510.319 568.129 600.409 626.429 20 484.334 584.392 390.297 538.360 568.381 610.427 644.441 404.276420.331435.157 464.326494.328 520.371 628.435 660.439 10 564.368 589.400608.411 682.449698.463716.472 388.284402.281421.140436.150450.311466.312 632.423 656.049 0 388.0 457.6 527.2 596.8 666.4 736.0 Mass (m/z)
Figure 50. MALDI MS spectrum of the UHPLC elute fraction at 42 minutes of the cationic tagged urine sample and the control of blank tagging reaction mixture.
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3-5.4. MALDI-MS spectra of a cationic tagged deconjugated urine sample
In the last part of this research, we directly compared MS spectra of the modified urine sample and the native urine sample. (Figure 51) The native urine sample was prepared by the procedure in section 3-3 without further modification. After solid phase extraction, the urine sample was directly spotted on MALDI sample plate and used for MS analysis in negative ionization mode. Many natural sulfate metabolite conjugates were detected in the negative mode, e.g., m/z = 367.157 represents sulfated testosterone (or the isomers prasterone and dehydroepiandrosterone) determined by exam mass and MS/MS fragments.
Native, negative mode TOF/TOF™ Reflector Spec #1 MC[BP = 395.0, 91737] 395.010 100 351.022 9.2E+ 90 397.007 80 353.020 367.157
70 399.054 60 438.998 375.060 50 % Intensity 440.997 40 378.100 359.065 467.209 30 350.014 496.072 383.153 471.240 20 369.158 379.109 415.140 10
0 348 379 410 441 472 503 Mass (m/z) <
80 379.093 80 209
70 70
60 60 50 Intensity
%
50 40
% Intensity 404.281 30 100 40 441.015 49 20 86 355 30 104 490.332 393.219 416.280 10 443.015451.336 20 0 9.0 111.4 213.8 316.2 418.6 521.0 Mass (m/z) 401.073 423.054 445.037 10 400.120 488.306 353.973 475.333 0 348 379 410 441 472 503 Mass (m/z) Figure 51. MALDI MS spectra of the unmodified urine sample and the cationic tagged urine sample. The amount of cationic tagged urine sample loaded for MS experiment is 1/120 of that used for native urine experiment. The red arrows indicate the sulfated testosterone/prasterone/dehydroepiandrosterone detected in the native urine sample and the cationic tagged molecule of the same metabolite in the modified urine sample. The inset is the MS/MS spectrum of the precursor ion (m/z = 492.348).
Page 105 of 133
Following the same sample preparation procedure, we prepared another urine sample for enzymatic deconjugation followed by CAX-B tagging. The cationic tagged sample was measured with MALDI MS.
Using the testosterone (desulfated and CAX-B tagged) as yardstick, we quantitatively evaluated the sensitivity of the MS analysis. The amount of the cationic tagged urine sample used for the positive mode
MALDI MS experiment is only 1/120 of the native urine used for negative mode MS experiment. However, the cationic tagged testosterone has saturated signal in the MS spectrum. This comparative study further demonstrates the value of deconjugation-cationic tagging of urine sample for MALDI MS analysis.
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4. SUMMARY AND CONCLUSION
In this dissertation work, it was demonstrated that an appropriate combination of sample preparation technology and UHPLC MALDI MS can provide a useful analytical platform for improved nontargeted metabolite discovery, including the exposome, of urine. A method was carefully designed, systematically evaluated, and fully optimized to furnish the first nontargeted analysis of environmental pollutants in urine. The method especially employed scaled up, competitive solid phase extraction of large urine samples under equilibrium conditions; enrichment of nonpolar sulfates by solid phase extraction under near-equilibrium conditions; optimized UHPLC MALDI analysis with enrichment injection; and deconjugation followed by cationic tagging of urine metabolites. This led to consistent data for complex samples. The optimized sample preparation method was used to detect more than one thousand sulfated metabolites by UHPLC MALDI MS analysis of urine samples, approximately twenty times more than detected in any previous study in a single analysis. Detection of the cationic tagged urine metabolites in the positive ionization mode of MALDI was 120-fold more sensitive than detection of the original natural sulfate conjugates in negative ionization mode. Further, an evaporative anionic tagging method was developed which greatly increased the sensitivity for detecting phenolic substances by MALDI-MS in a negative ionization mode. This work overall provides new methodology to analyze the urine metabolome, including some of the exposome, based on mass spectrometry, in a highly consistent way.
Thus, using UHPLC MALDI MS with the method described here, the detectable portion of total urine metabolome can be greatly expanded in new ways. By profiling and comparing metabolic patterns of a large number of urine samples, potentially one could perform statistical analysis to establish some new correlations between disease and exposure to pollutants. However, the statistical analysis is challenging.
The work reported here helps to make this challenge easier to overcome in the future by providing methodology which yields highly consistent data.
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5. PUBLICATIONS IN THIS STUDY
1. Yao, Y., Wang, P., Giese, R. (2014) Evaporative derivatization of phenols with 2-sulfobenzoic
anhydride for detection by MALDI-MS. Rapid Commun Mass Spectrom., 28(6), 653-661.
2. Wang, P., Zhang, Q., Yao, Y., Giese, R. (2015) Cationic xylene tag for increasing sensitivity in mass
spectrometry. J. Am. Soc. Mass. Spectrom. 26, 1713-1721.
3. Yao, Y., Wang, P., Gang, S., Anzalota Del Toro, L. V., Codero, J., Giese, R. (2016) Nontargeted
analysis of the urine nonpolar sulfateome: a pathway to the nonpolar xenobiotic exposome. Rapid
Commun Mass Spectrom.,30, 2341-2350.
4. Gang, G., McNeil, M., Yao, Y., Giese, R. (2016) Porous extraction paddle: a solid-phase extraction
technique for studying the urine metabolome. Rapid Commun Mass Spectrom.,30, 2462-2470.
5. Li, X., Yu, L., Kaeli, D., Yao, Y., Wang, P., Gang, G., Giese, R., Yusa, V., Alshawabkeh, A. (2016) A
framework for big metabolomic data management and analysis. International Journal on Advances in
Software,9, 50-60.
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6. REFERENCES
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