Capillary electrophoresis-mass spectrometry for proteomic and metabolic analysis

C H A P T E R

10 Capillary electrophoresis-mass spectrometry for proteomic and metabolic analysis Chenchen Wang, Cheng S. Lee Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, United States

O U T L I N E Analysis of metabolite profiles using capillary electrophoresis-mass spectrometry 171 Capillary zone electrophoresis-electrospray ionization-mass spectrometry 171 Sheath-liquid versus sheathless electrospray interfaces 172 Analysis of protein expression levels using capillary electrophoresis-mass spectrometry 173 Single-dimension capillary electrophoretic separation 173

Analysis of metabolite profiles using capillary electrophoresis-mass spectrometry Capillary zone electrophoresiselectrospray ionization-mass spectrometry Capillary zone electrophoresis (CZE) resolves analytes based on their differences in electrophoretic mobility, which is a function of the

Proteomic and Metabolomic Approaches to Biomarker Discovery https://doi.org/10.1016/B978-0-12-818607-7.00010-4

Capillary electrophoresis-based multidimensional separations

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Conclusion

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Update

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charge-to-size ratio. CZE equipped with a two-spectral channel laser-induced fluorescence detector has been employed for the simultaneous studies of two glycosphingolipid metabolic pathways in single primary neurons with unparallel detection sensitivities and at least six orders of magnitude of dynamic ranges.1 Due to its high throughput and excellent resolving power, the coupling of CZE with electrospray ionization-mass spectrometry

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Copyright # 2013 Elsevier Inc. All rights reserved.

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(ESI-MS)-enabled metabolomic profiling of single cells and subcellular structures such as single R2 neuron and metacerebral cell from Aplysia californica.2 CZE is particularly applicable for the separation of highly charged and hydrophilic metabolites that may not be retained in reversedphase liquid chromatography (RPLC). The identified metabolic features in human urine generally exhibit an m/z value in the range of 50–150 using CZE-ESI-MS. In contrast, 95% of the attributes detected by LC-MS have an m/z value above 150. CZE-ESI-MS therefore appears to be highly complementary to LC-MS, in providing the characterization of different classes of metabolites.3 CZE-ESI-MS was demonstrated for the search of metabolic indicators from urine in chronic patients with complex regional pain syndrome,4 the comprehensive profiling of free estrogens and their glucuronide/sulfate conjuagtes,5 and the discovery of urinary biomarkers for hepatotoxicity induced by drug therapy or exposure to toxicants.6 In addition to the analysis of urinary samples,3–6 conjugation of reduced thiols with various maleimide analogs was employed for increasing the ionization efficiency in conjunction with online sample preconcentration, allowing for sensitive and comprehensive determination of thiol redox status in plasma.7 Furthermore, various purification approaches, including methanol deproteinization, ultrafiltration, and solid phase extraction, were used prior to the analysis of metabolite profiles in human HT29 colon cancer cells.8 Important differences were observed in the metabolomic profiles obtained from solid-phase extraction and methanol deproteinization samples, indicating potential bias as the result of different purification strategies. A mouse multiple-tissue metabolome database, including the analyses of cerebra, cerebella, thymus, spleen, lung, liver, kidney, heart, pancreas, testis, and plasma from a single mouse, was developed using CZE-ESI-MS.9 Matrixassisted laser desorption/ionization time-of-flight

imaging mass spectrometry (MALDI-TOF-IMS) was combined with CZE- ESI-MS to determine contents of individual metabolites in serial tissue sections obtained from livers of super immune deficient mice.10 The combination of MALDI-TOF-IMS with CZE-ESI-MS was further employed for the visualization of spatiotemporal energy dynamics of hippocampal neurons by the analysis of energy-related metabolites during a kinetic-induced seizure.11 CZE-ESI-MS was demonstrated for performing quantitative metabolome profiling of colon and stomach tumor tissues.12 Quantification of 94 metabolites in colon and 95 metabolites in stomach involved in glycolysis, the pentose phosphate pathway, the tricarboxylic acid (TCA) and urea cycles, and amino acid and nucleotide metabolisms resulted in the identification of several cancer-specific metabolic traits. For the quantification of metabolites without purified standards, a multivariate strategy was introduced to derive a quantitative relationship between the measured relative response factor of polar metabolite and four physicochemical properties associated with ion evaporation.13 These properties include molecular volume, octanol-water distribution coefficient, absolute mobility, and effective charge.

Sheath-liquid versus sheathless electrospray interfaces The coupling of CZE to ESI-MS can be achieved via the use of sheath-liquid or a sheathless interface.14 The sheath-liquid interface is considered as a robust technique and has been most widely employed for CZE-ESI-MS measurements in metabolomics.15 However, intrinsic disadvantages of the sheath-liquid include the dilution of the CZE effluent and the potential induction of a hydrodynamic flow inside the capillary, thereby negatively affecting the achievable detection sensitivity and the resulting separation efficiency and resolution. In order to enable the detection of low-abundance

Analysis of protein expression levels using capillary electrophoresis-mass spectrometry

metabolites in body fluids, a number of research groups have therefore developed various sheathless interfaces.16–19 The work of Janini et al.16 and Sanz-Nebot et al.17 has illustrated the potential of the sheathless interface for the analysis of complex peptide mixtures. Moini has fabricated a porous capillary outlet by etching with hydrofluoric acid and established the electrical contact by protruding the porous tip from a stainless-steel ESI needled filled with static conductive liquid.18 Recently, Maxwell, Zhong, Chen, and colleagues20–22 designed an interface that is based on a stainless-steel hollow needle with a beveled sprayer tip for coupling CZE or capillary isoelectric focusing (CIEF) with ESI-MS. A detailed analytical evaluation of a sheathless interface on the basis of a porous tip18 was conducted by Busnel et al.23 for the analysis of tryptic digests of bovine serum albumin and Escherichia coli cell lysate. Sheathless CZE-ESI-MS was subsequently employed to enhance the coverage of the urinary metabolome by Ramautar and colleagues.24 Approximately 900 molecular features were detected in human urine by sheathless CZE-ESI-MS, whereas only about 300 molecular attributes were found with the use of a conventional sheath-liquid interface (Fig. 1). The integration of transient capillary isotachophoreis (CITP) as an in-capillary preconcentration procedure with sheathless CZE-ESI-MS provided further improvement in detection sensitivity, allowing the characterization of more than 1300 molecular features in urine.

Analysis of protein expression levels using capillary electrophoresis-mass spectrometry Single-dimension capillary electrophoretic separation CZE-ESI-MS was employed for the analysis of low-molecular-weight proteins (below 20 kDa)

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and peptides for the discovery of biomarkers in human urine. Samples were investigated from patients suffering from a variety of diseases, including ureteropelvic junction obstruction,25 cancer,26–28 vasculitis,29 coronary artery 30–32 kidney diseases,33–35 lithiumdiseases, graft-versus-host induced nephropathy,36 37 disease, and diabetes.32 The CZE-ESI-MS data were generally presented by plotting the measured molecular masses against their migration times and compared among healthy and diseased patients. Known and potential new urine biomarkers have been identified using subsequent MS/MS experiments.38,39 Although a variety of different proteins/peptides was discovered, most of these putative markers are derived from the most abundant proteins in the body such as collagen—mainly types I, II, and III, albumin, β-2-macroglobulin, and uromodulin.40 In addition to human urine, CZE-ESI-MS was also employed for the proteomic analysis of other body fluids such as human plasma41 and ventricular cerebrospinal fluid.42 Potential biomarkers of vascular disease in plasma from patients with chronic kidney disease were discovered.41 In contrast to the application of ESI-MS or ESI-MS/MS, offline MALDI-TOF/ TOF-MS coupled with iTRAQ labeling43 was demonstrated for multiplexed quantification of proteins in human ventricular cerebrospinal fluid samples collected from a patient with traumatic brain injury during patient recovery.42

Capillary electrophoresis-based multidimensional separations Based on the high orthogonality of two separations, the overall peak capacity is the multiplication product of the peak capacity of each individual separation dimension.44 Due to the proteome complexity of Mycobacterium marinum, CZE-ESI-MS was therefore used as the second separation dimension for further analysis of

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x106

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0

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FIG. 1 Base peak electropherograms of human urine obtained from (A) sheathless CZE-ESI-MS and (B) CZE-ESI-MS using a sheath-liquid interface.24

11 tryptic digestion fractions generated from RPLC.45 CZE again favors the identification of basic and hydrophilic peptides with low molecular masses and is highly complementary to RPLC toward the characterization of complex proteome mixtures. Capillary isoelectric focusing CIEF/nano-RPLC separations coupled with ESI-MS/MS have been developed and employed to achieve comprehensive and ultrasensitive analysis of minute protein digests extracted from

microdissected tissue specimens.46,47 In addition to protein identification, the use of label-freespectral counting approach48,49 to confidently and reproducibly quantify protein expression levels among tissues was evaluated by the measurements of coefficient of variation (CV) and the Pearson correlation coefficient.50 Analytical reproducibility of relative protein abundance was determined to exhibit a Pearson R2 value greater than .99 and a CV of 14.1%. The CIEF proteomic platform was capable of measuring changes in protein expression as low

Analysis of protein expression levels using capillary electrophoresis-mass spectrometry

as 1.5-fold with confidence as determined by t-test. The protein expression profiles from two distinct ovarian endometrioid tumor-derived cell lines have been compared using CIEF-based multidimensional separations coupled with ESI-MS/MS.51 Differentially expressed proteins were further investigated by ingenuity pathway analysis to reveal their association with important biological functions and signaling pathways such as the P13K/AKT pathway. The results illustrated the utility of high-throughput proteomic profiling combined with bioinformatics tools to provide insights into the mechanisms of deregulation in neoplastic cells. In addition to CIEF, microscale in-solution IEF was employed as the first separation dimension for the fractionation of intact proteins according to their isoelectric points, followed by proteolytic digestion with trypsin and subsequent CZE peptide separation coupled offline to MALDI-TOF/TOF-MS.52 The platform was used for the analysis of human follicular fluid with clinical implication. A total of 73 unique proteins were identified, including mostly acute-phase proteins and proteins that are known to be extensively involved in follicular development. Transient capillary isotachophoresis/ capillary zone electrophoresis Besides proteome complexity, the greatest bioanalytical challenge facing comprehensive proteomic analysis, particularly in the identification of low-abundance proteins, is related to the large variation of protein relative abundances. For example, the protein concentration dynamics range from 106-fold in cells to 1012fold in blood.53,54 In contrast to universally enriching all analytes by a similar degree, the result of the CITP stacking process is that major components may be diluted, but trace compounds are concentrated.55 Furthermore, CITP offers the benefits of speed and straightforward manipulation/switching between the stacking

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and separation modes in transient CITP/CZE. Transient CITP/CZE further provides seamless combination with nano-RPLC (Fig. 2) as two highly resolving and completely orthogonal separation techniques critically needed for analyzing human saliva and mouse brain mitochondrial proteomes.56,57 The ultrahigh resolving power of transient CITP/CZE as the first separation dimension has been demonstrated by significantly low peptide fraction overlapping for the analysis of protein expression within glioblastoma multiformederived cancer stem cells.58 Approximately 89% of distinct peptides were identified in only a single CITP fraction. In contrast, a high degree of peptide overlapping in strong cation exchange (SCX) chromatography, as the first separation dimension of the multidimensional protein identification technique (MuDPIT),59 was observed with at least 40% of carryover peptides that were identified in previous salt gradients. A high degree of peptide overlap in SCX unnecessarily burdens the subsequent nano-RPLC separation and greatly reduces the overall peak capacity in a multidimensional separation system. The CITP proteomic platform provided significant enhancements in total peptide, distinct peptide, and distinct protein identifications over a corresponding MuDPIT run by 119%, 192%, and 79%, respectively.58 The CITP proteomic technology, equipped with selective analyte enrichment and ultrahigh resolving power, further accomplished superior coverage in key pathways than that of the MuDPIT. For example, many biologically relevant proteins, including MKP, the Raf family, and Src in the ERK/ MAPK pathway, were identified only by the CITP technology (Fig. 3). Jinawath and colleagues60 have applied the CITP proteomic technology to perform comparative proteomic analysis of paired primary and recurrent postchemotherapy ovarian high-grade serous carcinomas from nine ovarian cancer patients. The increase in ovarian

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Syringe pump Microinjection valve 6 5

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Schematic of online integration of CITP with nano-RPLC for achieving selective analyte enrichment and multidimensional proteome separation. Solid and dashed lines represent the flow paths for the loading of CITP fractions and the injection of fractions into a nano-RPLC column, respectively.

cancer proteome coverage, attributed to CITPbased selective analyte enrichment, allowed the application of protein network and pathway analysis toward the discovery of ovarian carcinoma biomarkers. For example, lowabundance proteins such as cytokine IL-6 and signal transducer and activator of transcription 3 (STAT3), as well as many other proteins known to participate in the IL-6 signaling pathway, have been identified and compared for their expression levels within primary and recurrent ovarian tumors (Fig. 4).

The comparative proteomic results have further identified RELA, which is the p65 subunit of the NF-κB complex (Fig. 4). p65 was overexpressed more than threefold in recurrent tumors as compared to the primary tumors. The NF-κB/ RELA family of transcription factors is one of the most important and well-characterized signaling pathways in both normal and pathological conditions. It controls a variety of cellular functions, including inflammatory and immune responses, cell growth and survival, and drug resistance to several chemotherapeutic agents.61

Conclusion

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FIG. 3 Comparison of the coverage in the ERK/MAPK pathway achieved by the MuDPIT and CITP proteomic platform. Red: proteins only identified by CITP; blue: proteins identified by CITP with higher confidence (larger numbers of spectral counts and distinct peptide identifications per protein) than that achieved by MuDPIT; green: proteins identified by both CITP and MuDPIT with approximately equal confidence.58

Conclusion It has been well accepted that molecular profiling in tumor lesions is fundamental to understand the molecular etiology in tumor development and to provide the biomarkers for early detection and prevention. Furthermore, the need to detect small but biologically important changes in metabolites and proteins remains, as cancer researchers explore the initial steps in biological-signaling cascades and compensatory processes. Besides sample complexities, the greatest bioanalytical challenge facing

comprehensive proteomic and metabolomic analysis of tumor specimens is related to the identification and quantification of lowabundance metabolites and proteins. Developments in capillary electrophoresis-based single and multidimensional separations coupled with MS detection and sequencing are particularly highlighted for their roles within the broader context of state-of-the-art clinical proteomic efforts. The coupling of tissue microdissection for diseased cell enrichment with CITP-based selective analyte concentration not only presents a synergistic strategy toward the detection and

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IL-6 Signaling L8P

LFS

IL-6

TNF - a

IL-1

CD14 IL-1R

IL-GR

TNFR

Cytoplasm

RS TRAF6

SOS CRB2

TRAF2

CP130

SHC SAK

SHP2 P

TAX1

SOCS1

STAT3

TAB1 c-Raf

MKK417

NDC

MKK316 P STAT3

IMK

STAT3

STAT3

P38 MASK

MEK1/2

P

lks

JNK NF-kB

P

MASK APK2 STAT3 lks

STAT3

ERK1/2

P NF-kB

MSP27

Nucleus P JNK

STAT3

ERK-1/2

NF-kB

STAT3 P

EIK-1

NF-IL6

c-Jun

EIK-1 SRF

P

Transcription NF-IL6 CK2

c-Fos

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c-Jun NF-kB

IL-6RE

EIK-1 IL-6 IL-3

SRF SRF SRE

EBS

STAT3

P P P

STAT3 STAT3

STAT3 CRE

EBS TFE

Collagen type 1 TSCR

CYP19 MDR1

FIG. 4

Differentially expressed proteins among primary and recurrent ovarian tumors in the IL-6 signaling canonical pathway using the Ingenuity System.60

References

characterization of low-abundance metabolites and proteins but also offers a novel biomarker discovery paradigm toward the identification of tumor-associated markers, exploration of molecular relationships among different tumor states and phenotypes, and a deeper understanding of molecular mechanisms that drive cancer progression.

Update Over the last decade, significant advances in protein analysis for biomarker discovery have taken place, these techniques include capillary electrophoresis online with mass spectrometry (CE/MS), high-performance liquid chromatography (HPLC)/MS, ultra-performance liquid chromatography (UPLC)/MS, and gel electrophoresis in all its formats. The search of PubMed for CE/MS application as a technique for biomarker discovery produced a very limited number of hits. Most of the results dealt with protein and metabolite separations. In this section, we review the recent advances in CE/MS and their application to proteins and metabolites biomarkers search. A quick search of the scientific literature indicates that CE/MS has not be used as extensively as HPLC/MS or UPLC/MS. Here we present a selected number of references. Advances in protein analysis by CE and microchip electrophoresis were reviewed by Dawod et al.62 The review “highlights the progressions, new methodologies, innovative instrumental modifications, and challenges for efficient protein analysis in human specimens, animal tissues and plant samples.” The concentration of prostate-specific antigen (PSA) in serum is used as an early detection method for prostate cancer (PCa). However, PSA as a cancer biomarker has low specificity and sensitivity. Initial studies suggested that the glycosylation of PSA to be a promising

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marker for a more specific marker. Glycosylation is one of the most important posttranslational modifications for proteins. Kammeijr et al.63 presented a CE/ESI/MS method that will allow the relative quantitation of PSA glycoforms from urine. Wang et al.64 presented a minireview that highlighted the most recent advances in glycobiomarker studies to discover cancer-related glycosylation. A recently developed strategy, using sheathless CE-MS, could differentiate between different stages of polycystic kidney disease as well as changes in a variety of different metabolites, such as carnitine, glutamine, creatine, betaine, and creatinine.65

Acknowledgments We thank the National Cancer Institute (CA143177), the National Center for Research Resources (RR032333), and the National Institute of General Medical Sciences (GM103536) for supporting portions of our research activities reviewed in this article.

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